Information processing apparatus, information processing method, and information processing program

Abstract

To provide an information processing apparatus which can visualize correlation coefficients among elements with simple operation to output them.SOLUTION: The present invention is directed to an information processing apparatus having a reading unit for reading analysis target data in which data for a plurality elements including an explanatory variable and an objective variable are recorded, and a processing unit for calculating correlation coefficients among the two elements in the analysis target data read by the reading unit by using data of each of the elements to output the calculated correlation coefficients in a visualized mode.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus, an information processing method, and an information processing program.

Background Art

[0002] Techniques for data analysis have been disclosed. For example, Patent Document 1 discloses a technique of a data analysis support system that can narrow down unexpected rules from a huge number of correlation rules and quickly grasp useful information for business improvement and cause analysis.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When a complex event such as a chemical process occurs, for example, it is difficult to identify elements (for example, explanatory variables) that have a large impact on quality, or to confirm what kind of impact changing one element has on another element.

[0005] In view of the above points, the present disclosure has been made, and an object thereof is to provide an information processing apparatus, an information processing method, and an information processing program that can visualize and output the correlation coefficient between elements with a simple operation.

Means for Solving the Problems

[0006] According to an aspect of the present disclosure, there is provided an information processing apparatus including: a reading unit that reads analysis target data in which data is recorded for a plurality of elements including explanatory variables and target variables; and a processing unit that calculates a correlation coefficient between two of the elements in the analysis target data read by the reading unit using the data of each of the elements, and outputs the calculated correlation coefficient in a visualized state.

[0007] The processing unit may output the correlation coefficient in a visualized state by showing the data of the two elements in a predetermined number of two-dimensional graphs in descending order of the correlation coefficient.

[0008] In the two-dimensional graph, one axis may be an explanatory variable and the other axis may be a target variable.

[0009] The processing unit may output the correlation coefficient in a visualized state by showing a network diagram in which the elements are connected by lines according to the magnitude of the correlation coefficient between the elements.

[0010] The processing unit may show a network diagram in which the elements are connected by lines only when the value of the calculated correlation coefficient is equal to or greater than a predetermined threshold.

[0011] The processing unit may present a user interface for allowing a user to select elements for which the correlation coefficient is to be calculated.

[0012] According to another aspect of the present disclosure, there is provided an information processing method in which a processor reads analysis target data in which data is recorded for a plurality of elements including explanatory variables and target variables, calculates a correlation coefficient between two of the elements in the read analysis target data using the data of each of the elements, and executes a process of outputting the calculated correlation coefficient in a visualized state.

[0013] According to another aspect of the present disclosure, a computer is caused to execute a process of reading analysis target data in which data is recorded for a plurality of elements including explanatory variables and objective variables, calculating a correlation coefficient between two of the elements in the read analysis target data using the data of each of the elements, and outputting the calculated correlation coefficient in a visualized state. An information processing program is provided.

Advantages of the Invention

[0014] According to the present disclosure, it is possible to provide an information processing apparatus, an information processing method, and an information processing program that can visualize and output the correlation coefficient between elements with a simple operation.

Brief Description of the Drawings

[0015]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Embodiments for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the present disclosure will be described with reference to the drawings. In each drawing, the same or equivalent components and parts are given the same reference numerals. Also, the dimensional ratios in the drawings are exaggerated for convenience of explanation and may be different from the actual ratios.

[0017] FIG. 1 is a diagram showing a schematic configuration of an information processing apparatus according to the present embodiment. The information processing apparatus 10 executes information processing on analysis target data and outputs an analysis result as a result of the information processing. The information processing apparatus 10 is an example of a computer of the present disclosure, and is, for example, a personal computer in which a computer program for executing information processing on analysis target data is stored.

[0018] The analysis target data has a plurality of elements. Examples of elements include explanatory variables and objective variables. The explanatory variable and the objective variable together are also simply referred to as variables. In the present embodiment, the information processing apparatus 10 can use any data such as design data of a prototype and measurement data in a manufacturing process as the analysis target data.

[0019] The information processing apparatus 10 receives data in table format as the analysis target data. The data in table format may be stored in a database or may be entered in an arbitrary file such as a spreadsheet.

[0020] Then, the information processing apparatus 10 outputs the analysis result in a visualized state as a result of the information processing on the analysis target data. As the analysis result, the information processing apparatus 10 presents, for example, a two-dimensional graph showing the relationship between the elements according to the magnitude of the correlation coefficient between the elements of the analysis target data. Also, as the analysis result, the information processing apparatus 10 outputs, for example, a network diagram connecting the elements according to the magnitude of the correlation coefficient between the elements of the analysis target data.

[0021] The information processing apparatus 10 can execute information processing on the data to be analyzed and output the result of the information processing, so that the correlation coefficient between elements can be output in a visualized state with a simple operation for the user of the information processing apparatus 10.

[0022] Next, the hardware configuration of the information processing apparatus 10 will be described. FIG. 2 is a block diagram showing the hardware configuration of the information processing apparatus 10.

[0023] As shown in FIG. 2, the information processing apparatus 10 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a storage 14, an input unit 15, a display unit 16, and a communication interface (I / F) 17. Each component is connected to be communicable with each other via a bus 19.

[0024] The CPU 11 is a central processing unit that executes various programs and controls each unit. That is, the CPU 11 reads a program from the ROM 12 or the storage 14 and executes the program using the RAM 13 as a work area. The CPU 11 performs control of the above components and various arithmetic processes according to the program recorded in the ROM 12 or the storage 14. In the present embodiment, an information processing program for executing information processing on the data to be analyzed is stored in the ROM 12 or the storage 14.

[0025] The ROM 12 stores various programs and various data. The RAM 13 temporarily stores a program or data as a work area. The storage 14 is composed of a storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or a flash memory, and stores various programs including an operating system and various data.

[0026] The input unit 15 includes a pointing device such as a mouse and a keyboard, and is used to perform various inputs.

[0027] The display unit 16 is, for example, a liquid crystal display and displays various types of information. The display unit 16 may adopt a touch panel method and function as the input unit 15.

[0028] The communication interface 17 is an interface for communicating with other devices. For example, standards such as Ethernet (registered trademark), FDDI, Wi-Fi (registered trademark), etc. are used.

[0029] When executing the above information processing program, the information processing apparatus 10 realizes various functions using the above hardware resources. The functional configuration realized by the information processing apparatus 10 will be described.

[0030] FIG. 3 is a block diagram showing an example of the functional configuration of the information processing apparatus 10.

[0031] As shown in FIG. 3, the information processing apparatus 10 has a reading unit 101 and a processing unit 102 as functional configurations. Each functional configuration is realized by the CPU 11 reading and executing the information processing program stored in the ROM 12 or the storage 14.

[0032] The reading unit 101 performs a reading process of reading the data to be analyzed. The reading unit 101 may display, on the display unit 16, a user interface for causing the data to be analyzed to be read during the reading process. The user interface displayed by the reading unit 101 on the display unit 16 includes a user interface for allowing the user to select the data to be analyzed and a user interface for allowing the user to select the elements for which the correlation coefficient is to be calculated in the selected data to be analyzed. When the reading unit 101 displays a user interface for allowing the user to select the elements for which the correlation coefficient is to be calculated, the reading unit 101 displays, on the display unit 16, a user interface for allowing the user to select the target variable and the explanatory variables. Multiple explanatory variables can be selected.

[0033] The processing unit 102 executes information processing on the analysis target data read by the reading unit 101. In the present embodiment, as information processing, the processing unit 102 calculates a correlation coefficient between the target variable and the explanatory variable. Further, as information processing, the processing unit 102 calculates a correlation coefficient between variables. The processing unit 102 can calculate the correlation coefficient between the explanatory variable and the target variable by an arbitrary method. For example, the correlation coefficient is calculated using a PLS linear regression model by the PLS method (Partial Least Squares).

[0034] Then, as information processing, the processing unit 102 visually presents the relationship between the target variable and the explanatory variable, or the relationship between variables, to the display unit 16 using the calculated correlation coefficient. For example, the processing unit 102 presents a predetermined number of two-dimensional graphs showing the relationship between the target variable and the explanatory variable to the display unit 16 in descending order of the correlation coefficient, or in descending order of the absolute value of the correlation coefficient. Also for example, the processing unit 102 presents a network diagram to the display unit 16 such that the closer the variables are to each other, the larger the correlation coefficient between them is.

[0035] Note that the variables to be processed by the processing unit 102 may be selected by the user or used as they are, or the processing unit 102 may automatically select them based on a predetermined rule. For example, a variable whose name contains a predetermined character or symbol may be automatically selected by the processing unit 102 as a processing target.

[0036] Next, the operation of the information processing apparatus 10 will be described.

[0037] FIG. 4 is a flowchart showing the flow of information processing by the information processing apparatus 10. The CPU 11 reads an information processing program from the ROM 12 or the storage 14, expands it in the RAM 13, and executes it, thereby performing information processing.

[0038] The information processing shown in FIG. 4 is processing executed by the information processing apparatus 10 when calculating the correlation coefficient between the target variable and the explanatory variable and presenting a graph showing the relationship between the target variable and the explanatory variable.

[0039] In step S101, the CPU 11 reads analysis target data including a plurality of elements. The CPU 11 can read arbitrary data in a table format such as design data of a prototype and measurement data in a manufacturing process as the analysis target data.

[0040] Subsequent to step S101, in step S102, the CPU 11 causes the user to select an objective variable from among the elements of the analysis target data. When causing the user to select the objective variable, the CPU 11 presents a user interface for selecting the objective variable to the display unit 16.

[0041] Subsequent to step S102, in step S103, the CPU 11 causes the user to select an explanatory variable from among the elements of the analysis target data. When causing the user to select the explanatory variable, the CPU 11 presents a user interface for selecting the explanatory variable to the display unit 16. Note that when presenting the user interface to the display unit 16, the CPU 11 may present to the display unit 16 a user interface that allows the user to select the objective variable and the explanatory variable at once.

[0042] Subsequent to step S103, in step S104, the CPU 11 calculates a correlation coefficient between the explanatory variable and the objective variable selected by the user. The CPU 11 can calculate the correlation coefficient between the explanatory variable and the objective variable by an arbitrary method. For example, the correlation coefficient is calculated using a PLS linear regression model by the PLS method.

[0043] Subsequent to step S104, in step S105, the CPU 11 presents a predetermined number of two-dimensional graphs showing the relationship between the objective variable and the explanatory variable to the display unit 16 in descending order of the correlation coefficient or in descending order of the absolute value of the correlation coefficient. The predetermined number may be a preset threshold value. Further, the CPU 11 may present to the display unit 16 two-dimensional graphs in which the correlation coefficient or the absolute value of the correlation coefficient is equal to or greater than a predetermined threshold value in descending order of the correlation coefficient or in descending order of the absolute value of the correlation coefficient.

[0044] In the flowchart shown in FIG. 4, a graph was presented after calculating the correlation coefficient. However, the present disclosure is not limited to such an example. The CPU 11 may calculate the correlation coefficient between the objective variable and the explanatory variable when presenting the graph.

[0045] FIG. 5 is a flowchart showing the flow of information processing by the information processing apparatus 10. The CPU 11 reads an information processing program from the ROM 12 or the storage 14, expands it in the RAM 13, and executes it, thereby performing information processing.

[0046] The information processing shown in FIG. 5 is processing executed by the information processing apparatus 10 when calculating the correlation coefficient between the objective variable and the explanatory variable and presenting a graph showing the relationship between the objective variable and the explanatory variable.

[0047] In step S111, the CPU 11 reads analysis target data including a plurality of elements. The CPU 11 can read any data in table format such as design data of a prototype and measurement data in the manufacturing process as the analysis target data.

[0048] Subsequent to step S111, in step S112, the CPU 11 causes the user to select a plurality of variables to be analyzed from among the elements of the analysis target data. When causing the user to select variables, the CPU 11 presents a user interface for selecting variables on the display unit 16.

[0049] Subsequent to step S112, in step S113, the CPU 11 causes the user to select two variables from among the plurality of variables selected by the user in step S112, and calculates the correlation coefficient between the two variables. The CPU 11 calculates the correlation coefficient between two variables for all combinations of variables. That is, assuming that the number of variables selected by the user in step S112 is N, the CPU 11 N calculates C2 correlation coefficients.

[0050] Subsequent to step S113, in step S114, the CPU 11 causes the display unit 16 to display a network diagram in which the variables selected by the user in step S112 are positioned such that the closer the correlation coefficient is, the closer the positions are. When variables A, B, and C are selected by the user, if the correlation coefficients are large in the order of (A, B), (A, C), and (B, C), the CPU 11 causes the display unit 16 to display a network diagram in which variables A, B, and C are arranged such that the distances between variable A and variable B, between variable A and variable C, and between variable B and variable C become shorter in this order.

[0051] When the CPU 11 causes the display unit 16 to display the network diagram, it may be configured such that variables whose values are below a predetermined threshold are not connected by lines. By preventing variables whose values are below a predetermined threshold from being connected by lines, the CPU 11 can prevent the network diagram from becoming complicated.

[0052] Subsequently, an example of a user interface that the information processing apparatus 10 displays on the display unit 16 is shown. FIG. 6 is an example of a user interface that the information processing apparatus 10 displays on the display unit 16.

[0053] By displaying the user interface shown in FIG. 6 on the display unit 16, the information processing apparatus 10 can cause the user to set the explanatory variables and the target variable of the analysis target in the analysis target data to the information processing apparatus 10.

[0054] Subsequently, an example of the result of information processing that the information processing apparatus 10 displays on the display unit 16 is shown. FIG. 7 is a diagram showing an example of the result of information processing that the information processing apparatus 10 displays on the display unit 16, and is an example in which a predetermined number of two-dimensional graphs showing the relationship between the target variable and the explanatory variables are presented to the display unit 16 in descending order of the correlation coefficient or in descending order of the absolute value of the correlation coefficient. In each of the two-dimensional graphs shown in FIG. 7, the horizontal axis represents the explanatory variable and the vertical axis represents the target variable.

[0055] When presenting a plurality of graphs as shown in FIG. 7, the information processing apparatus 10 may plot them in color-coded manner according to the type of data used as explanatory variables. Examples of the type of data used as explanatory variables include devices, brands of materials, and the like. By plotting the graphs in color-coded manner according to the type of data, the information processing apparatus 10 can enable the user to visually and quickly confirm the characteristics of each device or brand that cannot be grasped only by the correlation coefficient.

[0056] By presenting a plurality of graphs as shown in FIG. 7, the information processing apparatus 10 can enable the user to visually grasp what explanatory variables have a large correlation coefficient with respect to the objective variable. That is, by presenting a plurality of two-dimensional graphs as shown in FIG. 7, it becomes possible to more easily enable the user to infer what explanatory variables affect the objective variable as compared with the case where the two-dimensional graphs as shown in FIG. 7 are not presented.

[0057] For example, when the analysis target data is data obtained by a chemical process, the information processing apparatus 10 can comprehensively extract the correlation relationships in the complex events occurring in the chemical process and enable the user to quickly grasp the factors (explanatory variables) that affect the quality.

[0058] FIG. 8 is a diagram showing an example of the result of information processing that the information processing apparatus 10 displays on the display unit 16, and is an example of a network diagram in which the variables selected by the user are closer to each other as the correlation coefficient is larger. In the network diagram shown in FIG. 8, the lines connecting the variables are shown thicker as the correlation coefficient is larger. Also, in the network diagram shown in FIG. 8, the line type or the color of the line may be changed depending on whether the correlation coefficient is positive or negative.

[0059] By presenting the network diagram as shown in FIG. 8, the information processing apparatus 10 can enable the user to visually grasp which variables have a large correlation coefficient. In other words, by presenting the network diagram as shown in FIG. 8, the information processing apparatus 10 can enable the user to visually grasp which variable affects which variable.

[0060] Also, although the two-dimensional graph shown in FIG. 7 shows the relationship between the explanatory variable and the objective variable, the network diagram shown in FIG. 8 can show not only the relationship between the explanatory variable and the objective variable but also the relationship between the explanatory variables. Therefore, when the manipulated variable is changed, the user can be made to infer the movement of each variable.

[0061] As described above, the embodiments of the present disclosure have been described in detail with reference to the accompanying drawings, but the technical scope of the present disclosure is not limited to such examples. It is obvious that those having ordinary knowledge in the technical field of the present disclosure can come up with various modification examples or correction examples within the scope of the technical idea described in the claims, and these modification examples or correction examples are naturally understood to belong to the technical scope of the present disclosure.

[0062] Also, the effects described in the above embodiments are illustrative or exemplary and are not limited to those described in the above embodiments. That is, the technology according to the present disclosure can exhibit other effects obvious to those having ordinary knowledge in the technical field of the present disclosure from the description in the above embodiments, together with or instead of the effects described in the above embodiments.

[0063] Note that, in each of the above embodiments, the information processing executed by the CPU by reading software (program) may be executed by various processors other than the CPU. Examples of the processor in this case include PLDs (Programmable Logic Devices) whose circuit configurations can be changed after manufacturing, such as FPGAs (Field-Programmable Gate Arrays), and dedicated electric circuits such as processors having circuit configurations designed specifically to execute specific processing, such as ASICs (Application Specific Integrated Circuits). Further, the information processing may be executed by one of these various processors, or may be executed by a combination of two or more processors of the same type or different types (for example, a plurality of FPGAs, and a combination of a CPU and an FPGA, etc.). More specifically, the hardware structure of these various processors is an electric circuit formed by combining circuit elements such as semiconductor elements.

[0064] Also, in each of the above embodiments, the mode in which the program for information processing is pre-stored (installed) in the ROM or the storage has been described, but the present invention is not limited to this. The program may be provided in a form recorded on a non-transitory recording medium such as a CD-ROM (Compact Disk Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), or a USB (Universal Serial Bus) memory. Further, the program may be in a form downloaded from an external device via a network.

Explanation of Reference Numerals

[0065] 10 Information processing apparatus 101 Reading unit 102 Processing unit

Claims

1. a reading unit that reads analysis target data in which data is recorded for a plurality of elements including explanatory variables and objective variables; a processing unit that calculates a correlation coefficient between two of the elements in the analysis target data read by the reading unit using data of each of the elements, and outputs the calculated correlation coefficient in a visualized state; An information processing device comprising:

2. The information processing device according to claim 1 , wherein the processing unit outputs the correlation coefficient in a visualized state by displaying data of two of the elements in descending order of the correlation coefficient in a predetermined number of two-dimensional graphs.

3. The information processing device according to claim 2 , wherein one axis of the two-dimensional graph is an explanatory variable and the other axis is a response variable.

4. The information processing device according to claim 1 , wherein the processing unit outputs the correlation coefficients in a visualized state by showing a network diagram in which the elements are connected by lines according to the magnitude of the correlation coefficients between the elements.

5. The information processing device according to claim 4 , wherein the processing unit displays a network diagram in which the elements are connected by lines only when the calculated value of the correlation coefficient is equal to or greater than a predetermined threshold value.

6. The information processing apparatus according to claim 1 , wherein the processing unit presents a user interface for allowing a user to select an element for which a correlation coefficient is to be calculated.

7. The processor: Load the data to be analyzed, which contains data recorded for multiple elements including explanatory variables and target variables. A correlation coefficient between two of the elements in the read analysis target data is calculated using data of each of the elements, and the calculated correlation coefficient is output in a visualized state. A method for processing information.

8. On the computer, Load the data to be analyzed, which contains data recorded for multiple elements including explanatory variables and target variables. A correlation coefficient between two of the elements in the read analysis target data is calculated using data of each of the elements, and the calculated correlation coefficient is output in a visualized state. An information processing program that executes processing.

Images