JP7269765B2 - Data visualization system and data visualization program - Google Patents

Description

The present invention relates to data visualization.

When performing data analysis such as failure detection or value prediction based on a data group, visualizing the data group makes it easier to determine the tendency or regularity of the data.
In order to visualize data, analysts need to think of the best graphs. However, when the amount of data is large or the content of the data is unclear, it is difficult to determine what kind of graph is optimal.

Patent Literature 1 discloses a technique for mechanically determining an optimum graph according to data.
In this method, the user inputs information such as the user's ID, the user's occupation, character information included in the graph, etc., and the input information is stored. Then, the optimum graph is mechanically determined based on the stored information when the same user uses the system from the next time onwards. As a result, it is possible to reduce the user's trouble in determining the optimum graph.

JP 2018-116657 A

The technique of Patent Literature 1 requires the user to input a lot of information such as the user's profile, character font, purpose of use, and so on. Therefore, it is conceivable that it takes a lot of time to input such information at the time of use. In addition, since only one graph is finally determined, it is difficult to deal with and improve when the desired graph is different from the determined graph.

SUMMARY OF THE INVENTION An object of the present invention is to enable effective visualization of data without prior information input by a user.

The data visualization system of the present invention is
a query reception unit that receives as an input query a query in which a plurality of elements extracted from a database are designated as an element set;
a search result acquisition unit that acquires, from the database, search results including one or more data sets corresponding to the element set specified in the input query;
an item element selection unit that selects, as an item element, an element to be assigned to the item axis of the graph from the element set based on the attribute of each element in the element set specified in the input query;
a numerical element selection unit that selects, as numerical elements, elements to be assigned to the numerical axis of the graph from the set of elements based on the attribute of each element in the set of elements specified in the input query;
A set of the item element data and the numerical element data is extracted from each data set included in the search result as a visualization data set, and one extracted from one or more data sets included in the search result a graph drawing unit that generates a visualization graph, which is a graph showing the relationship between the item element and the numerical element, using the above visualization data set, and displays the generated visualization graph on a display;

The item element selection unit calculates an item axis conformity, which is a degree of conformity with respect to the item axis, based on the attribute of each element of the element group, and calculates the item axis conformity based on the item axis conformity of each element of the element group. selecting the item element from the set of elements;
The numerical element selection unit calculates a numerical axis conformity, which is a degree of conformity with respect to a numerical axis, based on the attribute of each element of the element set, and calculates the numerical axis conformity based on the numerical axis conformity of each element of the element set. Select the numeric element from the set of elements.

The item element selection unit calculates, for each element of the element set, the item axis conformity of the element based on the data type of the element and the type of reserved word specified by the element in the input query,
The numerical element selection unit calculates, for each element of the element set, the numerical axis conformity of the element based on the data type of the element and the type of reserved word for which the element is specified in the input query.

The item element selection unit
selecting an element with the highest item axis compatibility from the element set as an item element candidate;
If one item element candidate is selected, determine the selected one item element candidate as the item element;
When two or more item element candidates are selected, the selected two or more item element candidates are displayed on the display, and one item element candidate selected from the displayed two or more item element candidates is displayed as described above. Decide on an item element.

The item element selection unit
selecting the highest item axis compatibility and the item axis compatibility within an approximation range from the item axis compatibility of each element of the element set, and
selecting an element having the selected item axis conformity as an item element candidate for each selected item axis conformity;
If one item element candidate is selected, determine the selected one item element candidate as the item element;
When two or more item element candidates are selected, the selected two or more item element candidates are displayed on the display, and one item element candidate selected from the displayed two or more item element candidates is displayed as described above. Decide on an item element.

The numerical element selection unit
Selecting an element with the highest degree of numerical axis compatibility from the element set as a numerical element candidate,
If one numerical element candidate is selected, determining the selected one numerical element candidate as the numerical element;
If two or more numerical element candidates are selected, each of the selected two or more numerical element candidates is determined as the numerical element.

The data visualization system extracts a log data group indicating the element name related to the numerical element from a log data set, which is a set of log data indicating the element name, graph type, and graph direction, and uses the extracted log data group a graph attribute determination unit that aggregates pairs of graph types and graph orientations, and determines pairs of graph types and graph orientations as graph attribute pairs based on the aggregation results;
The graph drawing unit generates the visualization graph according to the determined graph type and graph orientation of the graph attribute set.

The data visualization system includes a visualization learning unit,
The graph attribute determination unit determines a plurality of graph attribute sets based on the aggregation result,
The graph drawing unit displays a plurality of visualization graphs corresponding to the determined plurality of graph attribute sets,
The visualization learning unit receives a graph designation designating at least one visualization graph among the displayed plurality of visualization graphs, identifies a graph attribute set corresponding to the visualization graph designated by the received graph designation, Log data indicating the identified graph attribute set and the name of the numerical element is generated, and the generated log data is added to the log data set.

The data visualization system extracts a log data group indicating element names related to the numerical elements from a log data set, which is a set of log data indicating element names and graph types, and uses the extracted log data group to identify graph types. Equipped with a graph attribute determination unit that aggregates and determines the type of graph based on the aggregated results,
The graph drawing unit generates the visualization graph according to the determined graph type.

The data visualization system extracts a log data group indicating element names related to the numerical elements from a log data set, which is a set of log data indicating element names and graph directions, and uses the extracted log data groups to determine the graph directions. Equipped with a graph attribute determination unit that aggregates and determines the orientation of the graph based on the aggregation results,
The graph drawing unit generates the visualization graph according to the determined graph orientation.

The data visualization program of the present invention is
a query reception unit that receives as an input query a query in which a plurality of elements extracted from a database are designated as an element set;
a search result acquisition unit that acquires, from the database, search results including one or more data sets corresponding to the element set specified in the input query;
an item element selection unit that selects, as an item element, an element to be assigned to the item axis of the graph from the element set based on the attribute of each element in the element set specified in the input query;
a numerical element selection unit that selects, as numerical elements, elements to be assigned to the numerical axis of the graph from the set of elements based on the attribute of each element in the set of elements specified in the input query;
A set of the item element data and the numerical element data is extracted from each data set included in the search result as a visualization data set, and one extracted from one or more data sets included in the search result As a graph drawing unit that generates a visualization graph, which is a graph showing the relationship between the item elements and the numerical elements, using the above visualization data set, and displays the generated visualization graph on a display,
Make your computer work.

According to the present invention, data can be effectively visualized without prior information input by the user.

1 is a configuration diagram of a data visualization system 100 according to Embodiment 1. FIG. 1 is a configuration diagram of a data visualization device 200 according to Embodiment 1. FIG. 4 is a configuration diagram of a storage unit 290 according to Embodiment 1. FIG. 1 is a schematic diagram of a data visualization method according to Embodiment 1; FIG. 4 is a flowchart of a data visualization method according to Embodiment 1; 4 is a diagram showing the format of an SQL statement according to the first embodiment; FIG. 4 shows an input screen 121 according to Embodiment 1. FIG. 4 is a flowchart of item element selection processing (S130) according to Embodiment 1; 4 is a flowchart of step S132 in Embodiment 1; 4 is a flowchart of numerical element selection processing (S140) according to Embodiment 1; 4 is a flowchart of step S142 in Embodiment 1; 4 is a flowchart of graph attribute determination processing (S150) according to the first embodiment; 4 is a flowchart of graph drawing processing (S160) according to the first embodiment; 4 shows an output screen 122 according to the first embodiment; FIG. 4 is a flowchart of visualization learning processing (S170) according to Embodiment 1; FIG. 4 shows a table T in an example of the first embodiment; FIG. 4 is a diagram showing an SQL statement in example 1 of the first embodiment; FIG. FIG. 10 is a diagram showing a search result in Example 1 of Embodiment 1; FIG. FIG. 10 is a diagram showing a matching degree set in Example 1 of Embodiment 1; FIG. FIG. 4 is a diagram showing a log data group in Example 1 of Embodiment 1; FIG. FIG. 10 is a diagram showing a tallied result in Example 1 of Embodiment 1; FIG. FIG. 10 is a diagram showing information of a visualization graph group in Example 1 of Embodiment 1; FIG. FIG. 10 is a diagram showing a tallied result (second time) in Example 2 of Embodiment 1; FIG. FIG. 10 is a diagram showing a tallied result (third time) in Example 2 of Embodiment 1; FIG. FIG. 10 is a diagram showing information of a visualization graph group in Example 2 of Embodiment 1; FIG. 10 is a diagram showing an SQL statement in Example 3 of Embodiment 1; FIG. FIG. 10 is a diagram showing search results in Example 3 of Embodiment 1; FIG. 13 is a diagram showing a set of fitness levels in Example 3 of Embodiment 1; FIG. FIG. 10 is a diagram showing a log data group (parameter 1) in Example 3 of the first embodiment; FIG. FIG. 10 is a diagram showing a log data group (parameter 2) in Example 3 of the first embodiment; FIG. FIG. 13 is a diagram showing a log data group (parameter 3) in Example 3 of the first embodiment; FIG. FIG. 10 is a diagram showing a total result (parameter 1) in Example 3 of Embodiment 1; FIG. FIG. 12 is a diagram showing a total result (parameter 2) in Example 3 of Embodiment 1; FIG. FIG. 11 is a diagram showing a total result (parameter 3) in Example 3 of Embodiment 1; FIG. FIG. 11 is a diagram showing information of a visualization graph group in Example 3 of Embodiment 1; FIG. FIG. 11 is a diagram showing an SQL statement in Example 4 of Embodiment 1; FIG. FIG. 10 is a diagram showing search results in Example 4 of Embodiment 1; FIG. FIG. 13 is a diagram showing a set of fitness levels in Example 4 of Embodiment 1; FIG.

The same or corresponding elements are denoted by the same reference numerals in the embodiments and drawings. Descriptions of elements having the same reference numerals as those described will be omitted or simplified as appropriate. Arrows in the figure mainly indicate the flow of data or the flow of processing.

Embodiment 1.
The data visualization system 100 will be described based on FIGS. 1 to 38. FIG.

The data visualization system 100 is a system that visualizes data obtained by searching a database.

*** Configuration description ***
The configuration of the data visualization system 100 will be described based on FIG.
A data visualization system 100 includes a data visualization device 200 and a user terminal 110 .
The data visualization device 200 communicates with the user terminal 110 via the network 109 . Network 109 is, for example, the Internet.

A user terminal 110 is a terminal (computer) operated by a user of the data visualization system 100 .
The user instructs the data visualization device 200 to search the database by operating the user terminal 110 .
The user then analyzes the data visualized by the data visualization device 200 .

The data visualization device 200 searches a database and visualizes the data obtained by the search.

The configuration of the data visualization device 200 will be described based on FIG.
The data visualization device 200 is a computer having hardware such as a processor 201 , a memory 202 , an auxiliary storage device 203 , a communication device 204 and an input/output interface 205 . These pieces of hardware are connected to each other via signal lines.

A processor 201 is an IC that performs arithmetic processing and controls other hardware. For example, processor 201 is a CPU, DSP or GPU.
IC is an abbreviation for Integrated Circuit.
CPU is an abbreviation for Central Processing Unit.
DSP is an abbreviation for Digital Signal Processor.
GPU is an abbreviation for Graphics Processing Unit.

Memory 202 is a volatile storage device. Memory 202 is also referred to as main storage or main memory. For example, memory 202 is RAM. The data stored in memory 202 is saved in auxiliary storage device 203 as needed.
RAM is an abbreviation for Random Access Memory.

Auxiliary storage device 203 is a non-volatile storage device. For example, the auxiliary storage device 203 is ROM, HDD or flash memory. Data stored in the auxiliary storage device 203 is loaded into the memory 202 as required.
ROM is an abbreviation for Read Only Memory.
HDD is an abbreviation for Hard Disk Drive.

A communication device 204 is a receiver and a transmitter that realize communication of the data visualization device 200 . For example, communication device 204 is a communication chip or NIC.
NIC is an abbreviation for Network Interface Card.

The input/output interface 205 is a port to which an input device and an output device for realizing input/output of the data visualization device 200 are connected. For example, the input/output interface 205 is a USB terminal, the input device is a keyboard and mouse, and the output device is a display.
USB is an abbreviation for Universal Serial Bus.

The data visualization device 200 includes elements such as a query reception unit 210 , a search result acquisition unit 220 , a visualization analysis unit 230 , a graph drawing unit 240 and a visualization learning unit 250 . The visualization analysis unit 230 includes an item element selection unit 231 , a numeric element selection unit 232 and a graph attribute determination unit 233 . These elements are implemented in software.

The auxiliary storage device 203 stores a data visualization program for causing the computer to function as a query reception unit 210 , a search result acquisition unit 220 , a visualization analysis unit 230 , a graph drawing unit 240 and a visualization learning unit 250 . A data visualization program is loaded into memory 202 and executed by processor 201 .
The auxiliary storage device 203 further stores an OS. At least part of the OS is loaded into memory 202 and executed by processor 201 .
The processor 201 executes the data visualization program while executing the OS.
OS is an abbreviation for Operating System.

Input/output data of the data visualization program are stored in the storage unit 290 .
Memory 202 functions as storage unit 290 . However, a storage device such as the auxiliary storage device 203 , a register within the processor 201 and a cache memory within the processor 201 may function as the storage unit 290 instead of or together with the memory 202 .

The data visualization device 200 may include multiple processors that substitute for the processor 201 . A plurality of processors share the role of processor 201 .

The data visualization program can be recorded (stored) in a non-volatile recording medium such as an optical disc or flash memory in a computer-readable manner.

The configuration of the storage unit 290 will be described based on FIG.
The storage unit 290 stores a database 291, a log data set 292, and the like.

***Description of operation***
The operation of the data visualization system 100 corresponds to the data visualization method. Also, the procedure of the data visualization method corresponds to the procedure of the data visualization program.

Based on FIG. 4, an outline of the data visualization method will be described.
The query accepting unit 210 accepts queries from the user terminal 110 .
The search result acquisition unit 220 searches the database 291 using the query.
The visualization analysis unit 230 analyzes the graph to be visualized based on the query and search results.
The graph drawing unit 240 generates a group of graphs based on the search results and analysis results, and displays the group of graphs on the display of the user terminal 110 .
The visualization learning unit 250 receives designation of a graph selected from the graph group, and records log data related to the selected graph in the log data set 292 .

Based on FIG. 5, the procedure of the data visualization method will be described.
In step S<b>110 , the query accepting unit 210 accepts a query specifying a plurality of elements extracted from the database 291 .
Queries that are accepted are called "input queries." Specifically, the input query is a SQL statement. SQL is an abbreviation for Structured Query Language.
A plurality of elements specified in the input query is called an "element set". Specifically, an element set is a plurality of elements specified by a SELECT clause in an SQL statement.

FIG. 6 shows the format of the SQL statement.
The SQL statement includes a SELECT clause, a FROM clause, a GROUP BY clause, and the like. SQL statements can also include WHERE clauses, HAVING clauses and ORDER BY clauses.
"F1" and "F2" specified in the SELECT clause are database field names and correspond to "element set" in the embodiment.
"DATABASE" specified in the FROM clause is the name of the database and corresponds to the name of "database 291" in the embodiment.
"Fa" specified in the GROUP BY clause is the aggregate target axis. In one embodiment, one element is specified in the GROUP BY clause. In other words, the embodiment does not allow specification of multiple elements for the GROPU BY clause.

Returning to FIG. 5, the description of step S110 is continued.
The query accepting unit 210 accepts an input query as follows.
The user terminal 110 displays an input screen 121 as shown in FIG. 7 on the display.
The user enters an SQL statement into the input form on the input screen 121 and presses a send button.
The user terminal 110 transmits to the data visualization device 200 the SQL sentences entered in the input form on the input screen 121 .
The query reception unit 210 receives SQL sentences transmitted from the user terminal 110 . The received SQL statement becomes the input query.
However, the query accepting unit 210 may accept the input query by another method. For example, the query accepting unit 210 may accept an SQL statement input from an application program.

In step S120, the search result acquisition unit 220 acquires search results from the database 291 by executing the input query.
The search results include one or more data sets that correspond to the element set specified in the input query. The search results also include the data type of each element in the element set specified in the input query.
Specifically, the search result is a table obtained by executing the SQL statement. A data set included in the search result is one or more records included in the table.

In step S130, the item element selection unit 231 selects item elements from the element set based on the attribute of each element of the element set specified in the input query.
An item element is an element assigned to an item axis out of an item axis and a numerical value axis that constitute a graph.

The procedure of the item element selection process (S130) will be described with reference to FIG.
In step S131, the item element selection unit 231 selects one unselected element from the element set specified in the input query.
An element to be selected is called a "selected element".

In step S132, the item element selection unit 231 calculates the item axis conformity of the selected element based on the attribute of the selected element.
The item axis conformity is the degree of conformity to the item axis of the graph. In other words, the item axis conformity is the degree of conformity to the item axis of the graph.
Attributes of the selection element include the data type of the element and the type of reserved word with which the element is specified in the input query.

Element data types include "INT", "DEC", "DATE", "TIMESTAMP" and "CHAR".
"INT" means an integer.
"DEC" means floating point.
"DATE" means date.
"TIMESTAMP" means a time stamp.
"CHAR" means a fixed-length character string or a variable-length character string.

In addition to "SELECT" and "FROM", the types of reserved words include "WHERE", "GROUP BY", "ORDER BY", "ALL", "DISTINCT", "SUM", "COUNT" and "AVG "and so on.
In "WHERE", a condition is specified when the records are to be narrowed down. "WHERE" is described at the end of the sentence.
In "GROUP BY", an aggregation axis is specified when an aggregation function is specified for a column. An aggregation function is a function such as sum (SUM), maximum value (MAX) or average (AVG), and is used to aggregate data. Aggregate functions are also called set functions. Note that the phrase "HAVING" is used when specifying display conditions for the aggregated results. "GROUP BY" is described at the end of the sentence.
Columns to be totaled are specified in "ALL". Aggregation is performed by distinguishing records with the same value for the specified column. "ALL" is described at the beginning of the sentence.
"DISTINCT" designates a column to be aggregated. Records with the same value for the specified column are aggregated. "DISTINCT" is described at the beginning of the sentence.
"SUM" designates the columns to be summed. Prints the sum of the specified columns.
"COUNT" designates a column for which the number of records is to be obtained. Prints the number of records in the specified column.
"AVG" designates the column for which the average value is to be obtained. Outputs the average value of the specified column.

A specific example of step S132 will be described with reference to FIG.
In step S1321, the item element selection unit 231 determines whether the selected element follows the GROUP BY clause. That is, the item element selection unit 231 determines whether the selection element is specified by the GROUP BY clause.
If the selected element follows the GROUP BY clause, the item element selection unit 231 determines the item axis compatibility of the selected element to be "1.0".
If the selection element does not follow the GROUP BY clause, processing continues to step S1322.

In step S1322, the item element selection unit 231 determines whether the selected element is of the CHAR type and whether the data sets corresponding to the selected element are arranged at regular intervals in ascending order.
For example, it is assumed that a data string of "factory A, factory B, factory C" is obtained when data sets corresponding to selection elements are arranged in ascending order. In this case, the data sets corresponding to the selected elements are arranged at regular intervals in ascending order.
For example, assume that a data string "Kanagawa, Saitama, Tokyo" is obtained when the data sets corresponding to the selected elements are arranged in ascending order. In this case, the data sets corresponding to the selected elements are not evenly spaced in ascending order.
If the selected element is of the CHAR type and the data sets corresponding to the selected element are arranged at equal intervals in ascending order, the item element selection unit 231 determines the item axis compatibility of the selected element to be "0.8".
If the selected element is not of CHAR type and/or if the data sets corresponding to the selected element are not arranged at equal intervals in ascending order, the process proceeds to step S1323.

In step S1323, item element selection unit 231 determines whether the selected element is of DATE type or TIMESTAMP type.
If the selected element is of the DATE type or TIMESTAMP type, the item element selection unit 231 determines the item axis compatibility of the selected element to be "0.6".
If the selected element is neither DATE type nor TIMESTAMP type, the process proceeds to step S1324.

In step S1324, the item element selection unit 231 determines whether the selected element is of CHAR type.
When the selected element is of CHAR type, the item element selection unit 231 determines the item axis conformity of the selected element to be "0.5".
If the selected element is not of type CHAR, processing proceeds to step S1325.

In step S1325, the item element selection unit 231 determines whether the data sets corresponding to the selected elements are arranged at regular intervals in ascending order.
When the data sets corresponding to the selected elements are arranged at regular intervals in ascending order, the item element selection unit 231 determines the item axis compatibility of the selected elements to be "0.4".
If the data sets corresponding to the selected elements are not evenly spaced in ascending order, the process proceeds to step S1326.

In step S1326, the item element selection unit 231 determines whether the selected element is the leftmost column of the table (search result). That is, the item element selection unit 231 determines whether the selected element is the element specified at the beginning of the SELECT clause.
When the selected element is in the leftmost column of the table, the item element selection unit 231 determines the item axis conformity of the selected element to be "0.2".
When the selected element is not in the leftmost column of the table, the item element selection unit 231 determines the item axis conformity of the selected element to be "0.1".

Returning to FIG. 8, the description continues from step S133.
In step S133, the item element selection unit 231 determines whether there is an unselected element.
If there are unselected elements, the process proceeds to step S131.
If there are no unselected elements, the process proceeds to step S134.

In step S134, the item element selection unit 231 selects item elements based on the item axis conformity of each element.

The item element selection unit 231 selects item elements as follows.
The item element selection unit 231 selects an element having the highest degree of item axis conformity in the element set. Elements to be selected are called "item element candidates".
When one item element candidate is selected, the item element selection unit 231 determines the selected one item element candidate as the item element.
When two or more item element candidates are selected, the item element selection unit 231 displays the selected two or more item element candidates on the display of the user terminal 110 by communicating with the user terminal 110. . The user selects one item element candidate to be assigned to the item axis from the displayed two or more item element candidates. The item element selection unit 231 receives one selected item element candidate by communicating with the user terminal 110 . Then, the item element selection unit 231 determines the received one item element candidate as an item element.
However, if two or more item element candidates are selected, the data visualization device 200 may stop processing the data visualization method because two or more item axes cannot be provided in one graph.

The item element selection unit 231 may select item elements as follows.
First, the item element selection unit 231 selects, from the item axis conformity of each element in the element set, the highest item axis conformity and the item axis conformity in which the difference between the highest item axis conformity falls within the approximation range. do. The approximation range is a predetermined range for the item axis fit. For example, when the highest item axis matching degree in the element group is "0.6" and the approximation range is "0.1", the numerical element selection unit 232 selects "0.5 (=0.6-0 .1)” to “0.6” for each item axis fit.
Next, the item element selection unit 231 selects an element having the selected item axis compatibility for each selected item axis compatibility. Elements to be selected are called "item element candidates".
When one item element candidate is selected, the item element selection unit 231 determines the selected one item element candidate as the item element.
When two or more item element candidates are selected, the item element selection unit 231 displays the selected two or more item element candidates on the display of the user terminal 110 by communicating with the user terminal 110. . The user selects item element candidates to be assigned to the item axis from the displayed two or more item element candidates. The item element selection unit 231 receives selected item element candidates by communicating with the user terminal 110 . Then, the item element selection unit 231 determines the received item element candidate as an item element.

Returning to FIG. 5, the description continues from step S140.
In step S140, the numeric element selection unit 232 selects numeric elements from the element set based on the attribute of each element of the element set specified in the input query.
A numeric element is an element assigned to a numeric axis out of item axes and numeric axes that constitute a graph.

Based on FIG. 10, the procedure of the numerical element selection process (S140) will be described.
In step S141, the numeric element selection unit 232 selects one unselected element from the set of elements specified in the input query.
An element to be selected is called a "selected element".

In step S142, the numerical element selection unit 232 calculates the numerical axis matching degree of the selected element based on the attribute of the selected element.
Numeric axis fit is the fit to the numerical axis of the graph. In other words, the numerical axis conformity is the degree of conformity to the numerical axis of the graph.
Attributes of the selection element include the data type of the element and the type of reserved word with which the element is specified in the input query.

A specific example of step S142 will be described with reference to FIG.
In step S1421, numerical element selection section 232 determines whether the selected element is DATE type, TIMESTAMP type, or CHAR type.
If the selected element is of the DATE type, TIMESTAMP type, or CHAR type, the numerical element selection unit 232 determines the numerical axis matching degree of the selected element to be "0.1".
If the selected element is neither DATE type, TIMESTAMP type, nor CHAR type, the process proceeds to step S1422.

In step S1422, the numerical element selection unit 232 determines whether the selected element is of type INT and whether the data sets corresponding to the selected element are arranged at regular intervals in ascending order.
If the selected element is of type INT and the data sets corresponding to the selected element are arranged at equal intervals in ascending order, the numerical element selection unit 232 determines the numerical axis matching degree of the selected element to be "0.3".
If the selected element is not of type INT and/or if the data sets corresponding to the selected element are not arranged at equal intervals in ascending order, the process proceeds to step S1423.

In step S1423, the numerical element selection unit 232 determines whether the selected element is of the DEC type and whether the data sets corresponding to the selected element are arranged at regular intervals in ascending order.
If the selected element is of the DEC type and the data sets corresponding to the selected element are arranged at equal intervals in ascending order, the numerical element selection unit 232 determines the numerical axis conformity of the selected element to be "0.3".
If the selected element is not of the DEC type and/or if the data sets corresponding to the selected element are not arranged at equal intervals in ascending order, the numerical element selection unit 232 proceeds to step S1424.

In step S1424, the numeric element selection unit 232 determines whether the selected element is an aggregation function.
When the selected element is an aggregation function, the numerical element selection unit 232 determines the numerical axis conformity of the selected element to be "1.0".
If the selected element is not an aggregation function, the numerical element selection unit 232 determines the numerical axis matching degree of the selected element to be "0.6".

Returning to FIG. 10, the description continues from step S143.
In step S143, the numerical element selection unit 232 determines whether there is an unselected element.
If there are unselected elements, the process proceeds to step S141.
If there are no unselected elements, the process proceeds to step S144.

In step S144, the numerical element selection unit 232 selects numerical elements based on the degree of conformity to the numerical axis of each element.

The numerical element selection unit 232 selects numerical elements as follows.
The numerical element selection unit 232 selects an element with the highest degree of numerical axis matching from the element set. The elements to be selected are called "numerical element candidates".
When one numerical element candidate is selected, the numerical element selection unit 232 determines the selected one numerical element candidate as the numerical element.
When two or more numerical element candidates are selected, numerical element selection section 232 determines each of the selected two or more numerical element candidates as a numerical element.

Returning to FIG. 5, the description continues from step S150.
In step S150, the graph attribute determination unit 233 uses the log data set 292 to determine a graph attribute set to be applied to the visualized graph.
A graph attribute set is a set of a graph type and a graph orientation.

Graph types include bar graphs, pie graphs, scatter graphs, and line graphs.
A bar graph is a graph in which data of a certain element is represented by a rectangular figure.
A pie chart is a graph that represents the composition ratio of data by dividing a circular figure into sectors.
A scatter diagram is a graph that plots (dots) data by assigning different amounts (or sizes, etc.) to the vertical and horizontal axes.
A line graph is a kind of scatter diagram, and is a graph in which plots (points) of each data are connected by straight lines.

The orientation of the graph corresponds to the arrangement of the item axis and the value axis.
For example, in a bar graph, if the horizontal axis is the item axis and the vertical axis is the numerical value axis, the orientation of the bars representing data is "vertical". In this case, the orientation of the bar graph is "vertical".
For example, in a bar graph, if the vertical axis is the item axis and the horizontal axis is the numerical value axis, the orientation of the bars representing data is "horizontal". In this case, the orientation of the bar graph is "horizontal".

Based on FIG. 12, the procedure of the graph attribute determination process (S150) will be described.
In step S<b>151 , the graph attribute determination unit 233 extracts log data groups related to numerical elements from the log data set 292 .
A log data set 292 is a collection of log data.
The log data indicates the element name, graph type, and graph orientation.
The extracted log data group is one or more pieces of log data indicating element names related to numerical elements.
An element name for a numeric element is an element name that is the same as the name of the numeric element or an element name that is similar to the name of the numeric element.
A search for element names for numeric elements can be performed using a general technique of natural language processing. For example, wildcard searches or regular expressions can be used.

If no log data group related to numerical elements is found, all log data in the log data set 292 are treated as log data groups related to numerical elements.

In step S152, the graph attribute determination unit 233 aggregates pairs of graph types and graph orientations using the log data group regarding numerical elements.
That is, the graph attribute determining unit 233 counts the number of log data for each set of graph type and graph direction.

In step S153, the graph attribute determination unit 233 determines a graph attribute set based on the tallied result.
Specifically, the graph attribute determining unit 233 selects a prescribed number of sets from the sets of graph type and graph direction in descending order of aggregate value (number of log data). Each selected set is a determined graph attribute set.
The specified number is determined in advance. When the prescribed number is "3", the graph attribute determination unit 233 determines three graph attribute sets.

Returning to FIG. 5, the description continues from step S160.
In step S<b>160 , the graph drawing unit 240 generates a visualization graph for each determined graph attribute set, and displays each generated visualization graph on the display of the user terminal 110 .
A visualization graph is a graph showing the relationship between item elements and numerical elements.

Based on FIG. 13, the procedure of the graph drawing process (S160) will be described.
In step S161, the graph drawing unit 240 extracts a set of item element data and numerical element data from each data set included in the search results.
Each data set that is extracted is referred to as a "visualization data set."
One or more visualized data sets extracted from one or more data sets included in the search results are referred to as a "set of visualized data sets".

In step S162, graph drawing unit 240 selects one unselected graph attribute set from the graph attribute sets determined in step S150.
A selected graph attribute set is called a "selected attribute set".

In step S163, the graph drawing unit 240 uses the set of visualization data sets to generate a visualization graph according to the selected attribute set.
That is, the graph drawing unit 240 generates a visualization graph according to the graph type of the selected attribute group and the graph direction of the selected attribute group.
For example, it is assumed that the graph type of the selected attribute set is "bar graph" and the graph orientation of the selected attribute set is "vertical". In this case, the graph drawing unit 240 generates a bar graph in which numerical elements are assigned to the vertical axis and item elements are assigned to the horizontal axis.

In step S164, the graph drawing unit 240 determines whether there is an unselected graph attribute set.
If there is an unselected graph attribute set, the process proceeds to step S162.
If there is no unselected graph attribute set, the process proceeds to step S165.

One or more visualization graphs generated in steps S162 to S164 are referred to as a "visualization graph group".

In step S<b>165 , the graph drawing unit 240 causes the display of the user terminal 110 to display the visualized graph group by communicating with the user terminal 110 .

For example, assume that the visualization graph group is three visualization graphs. In this case, the graph drawing unit 240 transmits three visualized graphs to the user terminal 110. FIG.
Then, the user terminal 110 receives the three visualized graphs and displays an output screen 122 as shown in FIG. 14 on the display.
The output screen 122 contains three visualization graphs.

Returning to FIG. 5, step S170 will be described.
In step S<b>170 , the visualization learning unit 250 records in the log data set 292 log data relating to the visualization graph specified by the user among the displayed visualization graph group.

Based on FIG. 15, the procedure of the visualization learning process (S170) will be described.
In step S171, visualization learning unit 250 accepts graph designation.
The graph designation is data that designates at least one visualization graph among the displayed visualization graph group.

For example, the visualization learning unit 250 accepts graph designation as follows.
First, the user selects one visualization graph from the visualization graph group displayed on the output screen 122 (see FIG. 14).
Next, the user presses the decision button for the selected visualization graph by operating the user terminal 110 .
When any decision button is pressed, the user terminal 110 enlarges the visualized graph for the pressed decision button and displays it on the display. Also, the user terminal 110 transmits data including the identifier of the visualization graph corresponding to the pressed decision button to the data visualization device 200 . The data to be sent is the graph specification.
The visualization learning unit 250 then receives the graph specification transmitted from the user terminal 110 .

The output screen 122 is supplemented.
The output screen 122 has a "non-candidate" button. The "non-candidate" button is a button (graph change button) for displaying a different type of visualization graph from the displayed visualization graph group.
When the "non-candidate" button is pressed, the user terminal 110 requests the graph attribute list, and the graph attribute determination unit 233 responds with the graph attribute list. The graph attribute list is a list of pairs of graph types and graph directions.
When the graph attribute list is responded, the user terminal 110 displays the graph attribute list on the display. The user selects a set of graph type and graph orientation from the graph attribute list and designates the selected set. The specified set is called a "specified attribute set".
The user terminal 110 transmits attribute group designation to the data visualization device 200 . The attribute group specification is data indicating the specified attribute group.
The graph drawing unit 240 receives attribute group designation, generates a visualization graph according to the graph type and graph orientation designated by the attribute group designation, and transmits the generated visualization graph.
The user terminal 110 then receives the visualized graph and displays the received visualized graph on the output screen 122 .

In step S172, visualization learning unit 250 identifies a graph attribute set corresponding to the visualization graph designated by the received graph designation.

In step S173, the visualization learning unit 250 generates log data indicating the identified graph attribute set and the name of the numerical element.

In step S<b>174 , the visualization learning unit 250 adds the generated log data to the log data set 292 .

***Description of Examples***
An embodiment for visualizing data from sensors that measure the ambient temperature of each device in a factory will be described below.
FIG. 16 shows a table T stored in the database 291. As shown in FIG.
The "logdate" column indicates the date and time when the log was taken. "logdate" is of type TIMESTAMP.
The "location" column indicates where the log was taken. "location" is of type CHAR.
"parameter1" to "parameter3" indicate the position of the equipment.
The "parameter1" column indicates the coordinate X of the device. "parameter1" is of type INT.
The "parameter2" column indicates the coordinate Y of the device. "parameter2" is of type INT.
The "parameter3" column indicates the coordinate Z of the device. "parameter3" is of type INT.
The "temp" column indicates the temperature. "temp" is of type DEC.

<Example 1>
For the purpose of failure prediction, it is assumed that the ambient temperature of the equipment in "Mita" is displayed in chronological order.
FIG. 17 shows an SQL statement that becomes an input query.
A set of elements specified in the SQL statement is a set of "extract_dt (logdate)" and "temp".
An extract_dt function is defined in the SQL statement to remove unnecessary second information from the TIMESTAMP type logdate.
The TIMESTAMP type is recorded up to hours, minutes, and seconds, but the first embodiment does not require hours, minutes, and seconds. Therefore, logdate is converted to DATE type using the extract_dt function.

FIG. 18 shows a table resulting from the search.
The query receiving unit 210 receives an SQL statement (see FIG. 17), and the search result obtaining unit 220 executes the SQL statement. As a result, the table in FIG. 18 is obtained.
The obtained table includes a plurality of data sets corresponding to the set of "extract_dt(logdate)" and "temp".

FIG. 19 shows matching degree sets for “extract_dt(logdate)” and “temp”. A fitness set is a set of item axis fitness and numerical axis fitness.
The item element selection unit 231 calculates the item axis conformity shown in FIG. 19 according to the flowchart in FIG. Comparing the item axis conformity of "extract_dt(logdate)" and "temp", the item axis conformity of "extract_dt(logdate)" is greater. Therefore, the item element selection unit 231 selects "extract_dt (logdate)" as the item element.
The numerical element selection unit 232 calculates the numerical axis conformity shown in FIG. 19 according to the flowchart of FIG. Comparing the numerical axis conformity of "extract_dt(logdate)" and "temp", the numerical axis conformity of "temp" is greater. Therefore, the numerical element selection unit 232 selects "temp" as the numerical element.

FIG. 20 shows a log data group related to the numerical element "temp".
The graph attribute determining unit 233 extracts from the log data set 292 a log data group indicating element names that are the same as or similar to the numerical element name “temp”.

FIG. 21 shows the aggregation result of the log data group regarding the numerical element "temp".
The graph attribute determining unit 233 aggregates pairs of graph types and graph orientations using the log data group of FIG. 20 . The “number of appearances” corresponds to the number of corresponding log data.
The combination of "line graph" and "vertical" has the highest number of appearances "4". The graph attribute determination unit 233 determines the set of “line graph” and “vertical” as the first candidate graph attribute set.
The number of appearances "3" for the combination of "line graph" and "horizontal" is the second highest. The graph attribute determination unit 233 determines the set of “line graph” and “horizontal” as the second candidate graph attribute set.
The number of appearances "2" for the combination of "bar graph" and "vertical" is the third highest. The graph attribute determination unit 233 determines the set of “bar graph” and “vertical” as the third candidate graph attribute set.

FIG. 22 shows information of a visualization graph group displayed on the display of the user terminal 110. As shown in FIG.
The graph drawing unit 240 causes the display of the user terminal 110 to display visualized graphs of the first candidate, the second candidate, and the third candidate.
The first candidate visualized graph is a visualized graph corresponding to the first candidate graph attribute set.
The second candidate visualization graph is a visualization graph corresponding to the second candidate graph attribute set.
The visualization graph of the third candidate is the visualization graph corresponding to the graph attribute set of the third candidate.

<Example 2>
An example in which graph candidates are optimized by feedback processing of graph drawing information will be described.
Assume that the user has designated the third candidate visualization graph from the three visualization graphs displayed in <Example 1>.

The visualization learning unit 250 identifies a graph attribute set corresponding to the visualization graph of the third candidate. A graph attribute set corresponding to the visualization graph of the third candidate is a set of “bar graph” and “vertical”.
The visualization learning unit 250 adds to the log data set 292 log data indicating the identified graph attribute set “bar graph” and “vertical” and the numerical element “temp”.

Assume that a second data search is then performed using the SQL statement of FIG.
FIG. 23 shows the tabulation result at the time of the second data search.
The combination of "line graph" and "vertical" has the highest number of appearances "4". The graph attribute determination unit 233 determines the set of “line graph” and “vertical” as the first candidate graph attribute set.
The number of appearances "3" for the combination of "line graph" and "horizontal" is the second highest. The graph attribute determination unit 233 determines the set of “line graph” and “horizontal” as the graph attribute set A of the second candidate.
The number of appearances "3" for the combination of "bar graph" and "vertical" is the second highest. The graph attribute determination unit 233 determines the set of “bar graph” and “vertical” as the graph attribute set B of the second candidate.

The graph drawing unit 240 causes the display of the user terminal 110 to display visualization graphs of the first candidate, the second candidate A, and the second candidate B, respectively.
The first candidate visualized graph is a visualized graph corresponding to the first candidate graph attribute set.
The visualization graph of the second candidate A is the visualization graph corresponding to the graph attribute set A of the second candidate.
The visualization graph of the second candidate B is a visualization graph corresponding to the graph attribute set B of the second candidate.

It is assumed that the user has selected the visualization graph of the second candidate B from the displayed three visualization graphs.

The visualization learning unit 250 identifies a graph attribute set corresponding to the second candidate B visualization graph. A graph attribute set corresponding to the visualization graph of the second candidate B is a set of “bar graph” and “vertical”.
The visualization learning unit 250 adds to the log data set 292 log data indicating the identified graph attribute set “bar graph” and “vertical” and the numerical element “temp”.

After that, it is assumed that the third data retrieval by the SQL statement of FIG. 17 is performed.
FIG. 24 shows the tabulated result at the time of the third data search.
The combination of "line graph" and "vertical" has the highest number of appearances "4". The graph attribute determination unit 233 determines the set of “line graph” and “vertical” as the graph attribute set A of the first candidate.
The combination of “bar graph” and “vertical” has the highest number of appearances “4”. The graph attribute determination unit 233 determines the set of “bar graph” and “vertical” as the graph attribute set B of the first candidate.
The number of appearances "3" for the combination of "line graph" and "horizontal" is the third highest. The graph attribute determination unit 233 determines the set of “line graph” and “horizontal” as the third candidate graph attribute set.

FIG. 25 shows information of a visualization graph group displayed on the display of the user terminal 110. As shown in FIG.
The graph drawing unit 240 causes the display of the user terminal 110 to display visualization graphs of the first candidate A, the first candidate B, and the third candidate.
The visualization graph of the first candidate A is the visualization graph corresponding to the graph attribute set A of the first candidate.
The visualization graph of the first candidate B is a visualization graph corresponding to the graph attribute set B of the first candidate.
The visualization graph of the third candidate is the visualization graph corresponding to the graph attribute set of the third candidate.
Comparing the information in FIG. 25 with the information in FIG. 22, it can be seen that the order of the three visualized graph candidates to be displayed has changed.
In this way, the visualization learning unit 250 records the log data, thereby making it possible to present more suitable visualization graph candidates to the user.

<Example 3>
A case where there are multiple numerical element candidates will be described.
For the purpose of correlation analysis between parameters, it is assumed that other parameter values are checked when parameter 3 takes an abnormal value.
FIG. 26 shows an SQL statement that becomes an input query. The SQL statement in FIG. 26 is processed monthly.

FIG. 27 shows a table resulting from the search.
The query receiving unit 210 receives an SQL statement (see FIG. 26), and the search result obtaining unit 220 executes the SQL statement. As a result, the table in FIG. 27 is obtained.

FIG. 28 shows the fitness set of each element. A fitness set is a set of item axis fitness and numerical axis fitness.
The item element selection unit 231 calculates the item axis conformity shown in FIG. 28 according to the flowchart in FIG. The element with the highest item axis matching is "extract_dt (logdate)". Therefore, the item element selection unit 231 selects "extract_dt (logdate)" as the item element. However, since the difference in item axis matching between 'extract_dt(logdate)' and 'location' is as small as '0.1', the item element selection unit 231 uses 'extract_dt(logdate)' and 'location'. may be presented to the user, and the one specified by the user may be the item element.
The numerical element selection unit 232 calculates the numerical axis conformity shown in FIG. 28 according to the flowchart of FIG. Elements with the highest degree of numerical axis conformity are "parameter1", "parameter2" and "parameter3". In this case, the numerical element selection unit 232 selects the group of "parameter1", "parameter2", and "parameter3" as the numerical axis element group.

FIG. 29 shows a log data group regarding the numerical element "parameter1".
The graph attribute determining unit 233 extracts from the log data set 292 a log data group indicating element names that are the same as or similar to the numerical element name “parameter1”.
FIG. 30 shows a log data group regarding the numerical element "parameter2".
The graph attribute determining unit 233 extracts from the log data set 292 a log data group indicating element names that are the same as or similar to the numerical element name “parameter2”.
FIG. 31 shows a log data group related to the numeric element "parameter3".
The graph attribute determining unit 233 extracts from the log data set 292 a log data group indicating element names that are the same as or similar to the numerical element name “parameter3”.

FIG. 32 shows the aggregation result of the log data group regarding the numerical element "parameter1".
The graph attribute determining unit 233 aggregates pairs of graph types and graph directions using the log data group of FIG. 29 .
FIG. 33 shows the aggregation result of the log data group regarding the numerical element "parameter2".
The graph attribute determining unit 233 aggregates pairs of graph types and graph directions using the log data group of FIG. 30 .
FIG. 34 shows the aggregation result of the log data group regarding the numerical element "parameter3".
The graph attribute determining unit 233 uses the log data group of FIG. 31 to aggregate the sets of graph types and graph directions.
For each numerical element, the combination of “line graph” and “horizontal” has the highest number of occurrences. The graph attribute determination unit 233 determines the set of “line graph” and “horizontal” as the first candidate graph attribute set.
In each numerical element, the number of occurrences of the combination of "bar graph" and "vertical" is the second highest. The graph attribute determination unit 233 determines the set of “bar graph” and “vertical” as the second candidate graph attribute set.
For each numerical element, the combination of "bar graph" and "horizontal" has the third highest number of appearances. The graph attribute determination unit 233 determines the set of “bar graph” and “horizontal” as the third candidate graph attribute set.
If the order of the graph attribute set candidates differs for each numerical element, the graph attribute determination unit 233 determines the order of the graph attribute set candidates by majority vote among the numerical elements. However, the graph attribute determination unit 233 may determine the order of the graph attribute group candidates by other methods.

FIG. 35 shows information of a visualization graph group displayed on the display of the user terminal 110. As shown in FIG.
The graph drawing unit 240 causes the display of the user terminal 110 to display visualized graphs of the first candidate, the second candidate, and the third candidate.
Each visualization graph includes a graph for "parameter1", a graph for "parameter2" and a graph for "parameter3".

The user designates one of the displayed three visualization graphs.
The visualization learning unit 250 identifies a graph attribute set corresponding to the designated visualization graph, and adds log data indicating the identified graph attribute set and each numerical element (parameter1, parameter2 or parameter3) to the log data set 292. .

<Example 4>
A case where there are multiple item element candidates will be described.
It is assumed to confirm the correlation between the type of equipment and the temperature.
FIG. 36 shows an SQL statement that becomes an input query.

FIG. 37 shows a table resulting from the search.
The query receiving unit 210 receives an SQL statement (see FIG. 36), and the search result obtaining unit 220 executes the SQL statement. As a result, the table in FIG. 37 is obtained.

FIG. 38 shows the fitness set of each element. A fitness set is a set of item axis fitness and numerical axis fitness.
The numerical element selection unit 232 calculates the numerical axis conformity shown in FIG. 38 according to the flowchart of FIG. The element with the highest numerical axis matching is "temp". Therefore, the numerical element selection unit 232 selects "temp" as the numerical element.
The item element selection unit 231 calculates the item axis conformity shown in FIG. 38 according to the flowchart in FIG. Elements with the highest item axis matching are "location", "machine" and "status". In this case, the item element selection unit 231 presents "location", "machine", and "status" to the user, and determines the elements specified by the user as numerical elements. However, since it is impossible to assign all of “location”, “machine” and “status” to the item axis of the graph, the data visualization device 200 stops processing without displaying the visualization graph. may

***Description of modification***
The data visualization device 200 may be realized by multiple devices (computers). For example, the data visualization device 200 may not manage the database 291 and a server device that manages the database 291 may be provided separately from the data visualization device 200 .

The data visualization device 200 may be used as the user terminal 110 . In other words, the user may operate the data visualization device 200 instead of the user terminal 110 .

The graph attribute determination unit 233 may determine either the graph type or the graph orientation instead of the set of the graph type and the graph orientation.
For example, graph types are predetermined. The graph attribute determination unit 233 determines the orientation of the graph. The graph drawing unit 240 generates a visualization graph according to the predetermined graph type and the determined graph direction.
For example, the graph direction is predetermined for each graph type. The graph attribute determination unit 233 determines the type of graph. The graph drawing unit 240 generates a visualization graph according to the determined graph type and the graph direction corresponding to the determined graph type.

*** Effect of Embodiment 1 ***
Embodiment 1 can present one or more types of visualization graphs based on the input query, search results and log data set 292 .
Therefore, data can be effectively visualized without prior information input by the user.

*** Supplement to Embodiment 1 ***
The embodiments are examples of preferred modes and are not intended to limit the technical scope of the present invention. Embodiments may be implemented partially or in combination with other embodiments. The procedures described using flowcharts and the like may be changed as appropriate.

Each element of the data visualization device 200 may be implemented in software, hardware, firmware, or a combination thereof.
The “unit”, which is an element of the data visualization device 200, may be read as “processing” or “process”.

100 data visualization system, 109 network, 110 user terminal, 121 input screen, 122 output screen, 200 data visualization device, 201 processor, 202 memory, 203 auxiliary storage device, 204 communication device, 205 input/output interface, 210 query reception unit , 220 search result acquisition unit, 230 visualization analysis unit, 231 item element selection unit, 232 numeric element selection unit, 233 graph attribute determination unit, 240 graph drawing unit, 250 visualization learning unit, 290 storage unit, 291 database, 292 log data set.

Claims (13)

a query reception unit that receives as an input query a query in which a plurality of elements extracted from a database are designated as an element set;
a search result acquisition unit that acquires, from the database, search results including one or more data sets corresponding to the element set specified in the input query;
Calculate item axis compatibility, which is the degree of compatibility with the item axis, for each element of the element set specified in the input query, based on the attribute of the element; an item element selection unit that selects, from the element group, elements to be assigned to the item axis of the graph as item elements;
calculating a numerical axis conformity, which is a degree of conformity with respect to a numerical axis, based on the attribute of each element of the element set specified in the input query, and based on the numerical axis conformity of each element of the element set, a numerical element selection unit that selects an element to be assigned to the numerical axis of the graph as a numerical element from the element set;
A set of the item element data and the numerical element data is extracted from each data set included in the search result as a visualization data set, and one extracted from one or more data sets included in the search result a graph drawing unit that generates a visualization graph, which is a graph showing the relationship between the item elements and the numerical elements, using the above visualization data set, and displays the generated visualization graph on a display;
A data visualization system with The item element selection unit calculates, for each element of the element set, the item axis conformity of the element based on the data type of the element and the type of reserved word specified by the element in the input query,
3. The numerical element selection unit calculates, for each element of the element group, the numerical axis conformity of the element based on the data type of the element and the type of reserved word for which the element is specified in the input query. 2. The data visualization system according to 1 . The item element selection unit
selecting an element with the highest item axis compatibility from the element set as an item element candidate;
If one item element candidate is selected, determine the selected one item element candidate as the item element;
When two or more item element candidates are selected, the selected two or more item element candidates are displayed on the display, and one item element candidate selected from the displayed two or more item element candidates is displayed as described above. 3. The data visualization system according to claim 1 , wherein the item element is determined. The item element selection unit
selecting the highest item axis compatibility and the item axis compatibility within an approximation range from the item axis compatibility of each element of the element set, and
selecting an element having the selected item axis conformity as an item element candidate for each selected item axis conformity;
If one item element candidate is selected, determine the selected one item element candidate as the item element;
When two or more item element candidates are selected, the selected two or more item element candidates are displayed on the display, and one item element candidate selected from the displayed two or more item element candidates is displayed as described above. 3. The data visualization system according to claim 1 , wherein the item element is determined. The numerical element selection unit
Selecting an element with the highest degree of numerical axis compatibility from the element set as a numerical element candidate,
If one numerical element candidate is selected, determining the selected one numerical element candidate as the numerical element;
5. The data visualization system according to any one of claims 1 to 4 , wherein when two or more numerical element candidates are selected, each of the selected two or more numerical element candidates is determined as the numerical element. . a query reception unit that receives as an input query a query in which a plurality of elements extracted from a database are designated as an element set;
a search result acquisition unit that acquires, from the database, search results including one or more data sets corresponding to the element set specified in the input query;
an item element selection unit that selects, as an item element, an element to be assigned to the item axis of the graph from the element set based on the attribute of each element in the element set specified in the input query;
a numerical element selection unit that selects, as numerical elements, elements to be assigned to the numerical axis of the graph from the set of elements based on the attribute of each element in the set of elements specified in the input query;
A log data group indicating the element name of the numerical element is extracted from a log data set, which is a set of log data indicating the element name, the graph type, and the graph orientation, and the extracted log data group is used to determine the graph type and the graph orientation. a graph attribute determination unit that aggregates the pairs of and determines a pair of a graph type and a graph orientation as a graph attribute pair based on the aggregation result;
A set of the item element data and the numerical element data is extracted from each data set included in the search result as a visualization data set, and one extracted from one or more data sets included in the search result Using the above visualization data set, a visualization graph that is a graph showing the relationship between the item element and the numerical element is generated in accordance with the graph type and graph direction of the determined graph attribute set , and the generated visualization a graph drawing unit for displaying a graph on a display;
A data visualization system with The data visualization system includes a visualization learning unit,
The graph attribute determination unit determines a plurality of graph attribute sets based on the aggregation result,
The graph drawing unit displays a plurality of visualization graphs corresponding to the determined plurality of graph attribute sets,
The visualization learning unit receives a graph designation designating at least one visualization graph among the displayed plurality of visualization graphs, identifies a graph attribute set corresponding to the visualization graph designated by the received graph designation, 7. The data visualization system according to claim 6 , wherein log data indicating the identified graph attribute set and the name of the numerical element is generated, and the generated log data is added to the log data set. a query reception unit that receives as an input query a query in which a plurality of elements extracted from a database are designated as an element set;
a search result acquisition unit that acquires, from the database, search results including one or more data sets corresponding to the element set specified in the input query;
an item element selection unit that selects, as an item element, an element to be assigned to the item axis of the graph from the element set based on the attribute of each element in the element set specified in the input query;
a numerical element selection unit that selects, as numerical elements, elements to be assigned to the numerical axis of the graph from the set of elements based on the attribute of each element in the set of elements specified in the input query;
A log data group indicating the element name related to the numerical element is extracted from a log data set that is a set of log data indicating the element name and the graph type, the graph type is aggregated using the extracted log data group, and the aggregate result is a graph attribute determination unit that determines a graph type based on
A set of the item element data and the numerical element data is extracted from each data set included in the search result as a visualization data set, and one extracted from one or more data sets included in the search result Using the above visualization data set, a visualization graph that is a graph showing the relationship between the item elements and the numerical elements is generated in accordance with the determined graph type , and graph drawing for displaying the generated visualization graph on the display. Department and
A data visualization system with a query reception unit that receives as an input query a query in which a plurality of elements extracted from a database are designated as an element set;
a search result acquisition unit that acquires, from the database, search results including one or more data sets corresponding to the element set specified in the input query;
an item element selection unit that selects, as an item element, an element to be assigned to the item axis of the graph from the element set based on the attribute of each element in the element set specified in the input query;
a numerical element selection unit that selects, as numerical elements, elements to be assigned to the numerical axis of the graph from the set of elements based on the attribute of each element in the set of elements specified in the input query;
A log data group indicating the element name of the numerical element is extracted from the log data set, which is a set of log data indicating the element name and the graph orientation, and the graph orientation is aggregated using the extracted log data group, and the aggregation result is obtained. a graph attribute determination unit that determines the graph orientation based on
A set of the item element data and the numerical element data is extracted from each data set included in the search result as a visualization data set, and one extracted from one or more data sets included in the search result Using the above visualization data set, a visualization graph that is a graph showing the relationship between the item elements and the numerical elements is generated in accordance with the determined graph orientation , and graph drawing for displaying the generated visualization graph on the display. Department and
A data visualization system with a query reception unit that receives as an input query a query in which a plurality of elements extracted from a database are designated as an element set;
a search result acquisition unit that acquires, from the database, search results including one or more data sets corresponding to the element set specified in the input query;
Calculate item axis compatibility, which is the degree of compatibility with the item axis, for each element of the element set specified in the input query, based on the attribute of the element; an item element selection unit that selects, from the element group, elements to be assigned to the item axis of the graph as item elements;
calculating a numerical axis conformity, which is a degree of conformity with respect to a numerical axis, based on the attribute of each element of the element set specified in the input query, and based on the numerical axis conformity of each element of the element set, a numerical element selection unit that selects an element to be assigned to the numerical axis of the graph as a numerical element from the element set;
A set of the item element data and the numerical element data is extracted from each data set included in the search result as a visualization data set, and one extracted from one or more data sets included in the search result As a graph drawing unit that generates a visualization graph, which is a graph showing the relationship between the item elements and the numerical elements, using the above visualization data set, and displays the generated visualization graph on a display,
A data visualization program that makes computers work. a query reception unit that receives as an input query a query in which a plurality of elements extracted from a database are designated as an element set;
a search result acquisition unit that acquires, from the database, search results including one or more data sets corresponding to the element set specified in the input query;
an item element selection unit that selects, as an item element, an element to be assigned to the item axis of the graph from the element set based on the attribute of each element in the element set specified in the input query;
a numerical element selection unit that selects, as numerical elements, elements to be assigned to the numerical axis of the graph from the set of elements based on the attribute of each element in the set of elements specified in the input query;
A log data group indicating the element name of the numerical element is extracted from a log data set, which is a set of log data indicating the element name, the graph type, and the graph orientation, and the extracted log data group is used to determine the graph type and the graph orientation. a graph attribute determination unit that aggregates the pairs of and determines a pair of a graph type and a graph orientation as a graph attribute pair based on the aggregation result;
A set of the item element data and the numerical element data is extracted from each data set included in the search result as a visualization data set, and one extracted from one or more data sets included in the search result Using the above visualization data set, a visualization graph that is a graph showing the relationship between the item element and the numerical element is generated in accordance with the graph type and graph direction of the determined graph attribute set , and the generated visualization As a graph drawing part that displays the graph on the display,
A data visualization program that makes computers work. a query reception unit that receives as an input query a query in which a plurality of elements extracted from a database are designated as an element set;
a search result acquisition unit that acquires, from the database, search results including one or more data sets corresponding to the element set specified in the input query;
an item element selection unit that selects, as an item element, an element to be assigned to the item axis of the graph from the element set based on the attribute of each element in the element set specified in the input query;
a numerical element selection unit that selects, as numerical elements, elements to be assigned to the numerical axis of the graph from the set of elements based on the attribute of each element in the set of elements specified in the input query;
A log data group indicating the element name related to the numerical element is extracted from a log data set that is a set of log data indicating the element name and the graph type, the graph type is aggregated using the extracted log data group, and the aggregate result is a graph attribute determination unit that determines a graph type based on
A set of the item element data and the numerical element data is extracted from each data set included in the search result as a visualization data set, and one extracted from one or more data sets included in the search result Using the above visualization data set, a visualization graph that is a graph showing the relationship between the item elements and the numerical elements is generated in accordance with the determined graph type , and graph drawing for displaying the generated visualization graph on the display. as a department
A data visualization program that makes computers work. a query reception unit that receives as an input query a query in which a plurality of elements extracted from a database are designated as an element set;
a search result acquisition unit that acquires, from the database, search results including one or more data sets corresponding to the element set specified in the input query;
an item element selection unit that selects, as an item element, an element to be assigned to the item axis of the graph from the element set based on the attribute of each element in the element set specified in the input query;
a numerical element selection unit that selects, as numerical elements, elements to be assigned to the numerical axis of the graph from the set of elements based on the attribute of each element in the set of elements specified in the input query;
A log data group indicating the element name of the numerical element is extracted from the log data set, which is a set of log data indicating the element name and the graph orientation, and the graph orientation is aggregated using the extracted log data group, and the aggregation result is obtained. a graph attribute determination unit that determines the graph orientation based on
A set of the item element data and the numerical element data is extracted from each data set included in the search result as a visualization data set, and one extracted from one or more data sets included in the search result Using the above visualization data set, a visualization graph that is a graph showing the relationship between the item elements and the numerical elements is generated in accordance with the determined graph orientation , and graph drawing for displaying the generated visualization graph on the display. as a department
A data visualization program that makes computers work.

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