Patent Application
20240282134
The present invention relates to a determination device, a determination method, and a determination program.
Conventionally, there has been known a process mining method of analyzing and visualizing a flow of work performed in business to find an improvement point in the business. Information used for analysis and visualization in such a process mining method is a log in which an event to be analyzed is recorded. For example, there are various events to be analyzed depending on a type of business and granularity to be analyzed, but for example, a graphical user interface (GUI) operation may be targeted, such as “clicking a button” or “inputting to a text box”.
The log used for process mining needs to satisfy, for example, requirements that the log is “narrowed down to only information to be analyzed”, “divided for each case”, and “in a state where an event can be identified”. For example, an operation log in which an operation on a personal computer (PC) is recorded often does not satisfy the requirements of the log used for the process mining. For that reason, when the process mining is performed, for example, the operation log needs to be processed to satisfy the requirements by three pieces of pre-processing, “removal of an unnecessary operation event”, “determination of identical operation events”, and “division in units of cases”.
Here, processing of “determination of an identical operation” is processing of determining operations having an identical meaning in the operation log and making the operations identifiable as work events. That is, in the operation log, only information of the GUI at the time of recording is recorded as it is, and thus, all the operations are separate events in an initial state. For that reason, it is necessary to perform processing of identifying identical events in consideration of meanings of operations in work. Conventionally, in analysis and visualization of an operation on a PC for finding an improvement point in business, a person manually performs processing of connecting identical operation events with each other, for example, by visually confirming an operation log and adding a unique operation type ID to a plurality of events regarded as identical.
Non Patent Literature 1: Yokose, Urabe, Yagi, et al., “Business visualization technology contributing to DX promotion”, 2020, NTT Technical Journal, 2020 vol.32 No. 2, p. 72-75, [online], [Searched on Apr. 23, 2021], Internet <https://journal.ntt.co.jp/article/880>
However, in the above-described conventional technique, the identical operation events cannot be easily connected with each other in the pre-processing for the process mining. This is because the above-described conventional technique has the following problems.
First, since identical operations cannot be determined on the operation log, it is necessary to connect the identical operation events with each other. In addition, it is possible to manually connect them with each other one by one, but in a case where there are a large amount of logs, it is difficult to manually connect them with each other all.
On the other hand, since systems to be analyzed in the process mining have different internal structures, connection cannot be automatically determined by a fixed rule algorithm. In addition, it is also possible to cope with this by manually customizing the rule algorithm in accordance with the internal structures and work of the systems, but it is necessary to understand the internal structures of the systems and meanings of attribute values included in the operation log, so that it is difficult for a general user.
To solve the above-described problems and achieve an object, a determination device according to the present invention includes: a reception unit that receives log events; an estimation unit that estimates a determination criterion for determining identity of the log events on the basis of an attribute value of a log included in the log events; and a determination unit that determines identity for a log event to be processed on the basis of the determination criterion.
In addition, a determination method according to the present invention is a determination method executed by a determination device, and the determination method includes: a process of receiving log events; a process of estimating a determination criterion for determining identity of the log events on the basis of an attribute value of a log included in the log events; and a process of determining identity for a log event to be processed on the basis of the determination criterion.
In addition, a determination program according to the present invention causes a computer to execute: a step of receiving log events; a step of estimating a determination criterion for determining identity of the log events on the basis of an attribute value of a log included in the log events; and a step of determining identity for a log event to be processed on the basis of the determination criterion.
In the present invention, the identical operation events can be easily connected with each other in the pre-processing for the process mining.
Hereinafter, embodiments of a determination device, a determination method, and a determination program according to the present invention will be described in detail with reference to the drawings. In addition, the present invention is not limited to the embodiments described below.
Hereinafter, processing performed by a determination system, a configuration of a determination device 10, details of each of pieces of processing, and a flow of each of pieces of processing according to a first embodiment (as appropriate, a present embodiment) will be sequentially described, and finally, effects of the present embodiment will be described.
Hereinafter, processing performed by the determination system (as appropriate, the present system) according to the present embodiment will be described. The present system is used for processing an operation log in which an operation on a PC is recorded, and particularly executes automatic determination processing for identical operation events by the user's exemplification. Hereinafter, the processing performed by the present system will be described in comparison with a conventional technique.
The process mining method for business analysis described above is widely used in the market. In addition, there is also a mechanism for recording the operation on the PC as a log (operation log). At this time, pre-processing may be required to perform process mining on the operation log. That is, since identical operations cannot be determined on the operation log, it is necessary to connect identical operation events with each other. In addition, it is possible to manually connect them with each other one by one, but in a case where there are a large amount of logs, it is difficult to manually connect them with each other all.
On the other hand, since systems to be analyzed in the process mining have different internal structures, connection cannot be automatically determined by a fixed rule algorithm. In addition, it is also possible to cope with this by manually customizing the rule algorithm in accordance with the internal structures and work of the systems, but it is necessary to understand the internal structures of the systems and meanings of attribute values included in the operation log.
Thus, in the present system, the following processing is executed. First, a user is caused to exemplify a plurality of common operation events, that is, operation events for which identity is determined. Second, a rule for determining a connection is estimated from a relationship of attribute values between the exemplified operation events. Third, the identical operation events are automatically determined by using the estimated rule. According to the above processing, it is possible to automatically perform connection of the identical operation events by the user's exemplification even if there is no deep understanding of an internal structure of a system to be analyzed and the attribute values of the operation log.
A configuration of the determination device 10 according to the present embodiment will be described in detail with reference to
The input unit 11 manages input of various types of information to the determination device 10. For example, the input unit 11 is implemented by a mouse, a keyboard, or the like, and receives an input of setting information or the like to the determination device 10. In addition, the output unit 12 manages output of various types of information from the determination device 10. For example, the output unit 12 is implemented by a display or the like, and outputs setting information or the like stored in the determination device 10.
The communication unit 13 manages data communication with other devices. For example, the communication unit 13 performs data communication with each of communication devices. In addition, the communication unit 13 can perform data communication with an operator's terminal (not illustrated).
The storage unit 14 stores various types of information referred to when the control unit 15 operates, and stores various types of information acquired when the control unit 15 operates. Here, the storage unit 14 can be implemented by, for example, a semiconductor memory device such as a random access memory (RAM) or a flash memory, a storage device such as a hard disk or an optical disk, or the like. Note that, in the example of
The storage unit 14 stores an operation log to be processed. For example, the storage unit 14 stores, as the operation log, “occurrence time” of the operation, “unique information on an operated GUI component”, and the like. In addition, in the operation log, information on one operation event is expressed as a collection of a plurality of attribute values (columns, items).
Here, the operation log stored in the storage unit 14 will be described with reference to
Note that, in the operation log, in addition to a GUI operation on the PC, input by some input device may be recorded, or command input on a character-based user interface (CUI) may be recorded. In a case of recording these other types of operations, it is necessary to increase the number of log items as necessary.
As illustrated in
In the example of
The control unit 15 manages control of the entire determination device 10. The control unit 15 includes a reception unit 15a, an estimation unit 15b, and a determination unit 15c. Here, the control unit 15 is, for example, an electronic circuit such as a central processing unit (CPU) or a micro processing unit (MPU), or an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).
The reception unit 15a receives an operation event as a log event. For example, the reception unit 15a receives images of operation events associated with each other by a user as identical operations among images of a plurality of operation events. That is, the reception unit 15a receives, among captured images of a plurality of operation events displayed in chronological order, a combination of the captured images associated with each other by the user as identical operations. Here, the log event is an event including a log having a similar structure (for example, a reception/transmission history of a telephone, and the like) in addition to the operation event.
Describing using a specific example, in a case where a plurality of operation events is selected by a click operation by the user on the captured images visually displayed chronologically on a screen of the user's terminal, the reception unit 15a receives operation logs of operation events associated with the selected captured images as “identical operation logs”. Further, in a case where a plurality of other operation events is selected, the reception unit 15a receives operation logs of operation events associated with the selected captured images as other “identical operation logs”. Note that reception processing described above will also be described in detail in [Details of each of pieces of processing] (1. Processing of receiving exemplification by connection of operation events) described later.
The reception unit 15a refers to the operation log stored in the storage unit 14 and acquires a selected operation log. On the other hand, the reception unit 15a outputs a set of selected operation logs to the estimation unit 15b. Note that the reception unit 15a may store the set of the selected operation logs in the storage unit 14.
The estimation unit 15b estimates, as a log event, a determination criterion (rule) for determining the identity of the operation events on the basis of the attribute value of the operation log included in the operation. For example, the estimation unit 15b estimates a determination criterion for determining the identity of the operation events by extracting the attribute value common of the operation log. That is, the estimation unit 15b estimates a first determination criterion in the set of operation events associated with each other as the identical operations by extracting a character string or a numerical range commonly included in attribute elements in accordance with a condition set for each of the attribute elements. Further, the estimation unit 15b estimates a second determination criterion between sets of operation events associated with each other as the identical operations by performing comparison of the first determination criterion.
Describing using a specific example, in a case where a character string “input” common to all is included as an attribute value of an attribute element “operation type” (rule type A: determine a character string by an exact match) in a plurality of operation logs received as identical operation events by the reception unit 15a, the estimation unit 15b estimates an operation event in which the attribute element “operation type” exactly matches, as a determination criterion (first determination criterion) in an identical operation set. In addition, in a case where the attribute element “operation type” exactly matches between sets of the plurality of operation logs received as the identical operation events by the reception unit 15a, the estimation unit 15b estimates an operation event in which the attribute element “operation type” exactly matches, as a determination criterion (second determination criterion) between identical operation sets, that is, a final determination criterion. Note that estimation processing described above will also be described in detail in [Details of each of pieces of processing] (4. Rule estimation processing for each attribute value) described later.
In addition, the estimation unit 15b acquires a set of operation logs output by the reception unit 15a and a rule type of the attribute value stored in the storage unit 14, and extracts a character string or a numerical range commonly included as a determination criterion. Further, the estimation unit 15b may extract a pattern in which a set of a plurality of operation logs satisfies the rule type of the attribute value as the determination criterion. On the other hand, the estimation unit 15b outputs the extracted determination criterion to the determination unit 15c. Note that the estimation unit 15b may store the extracted determination criterion in the storage unit 14.
The determination unit 15c determines the identity for an operation event to be processed as a log event to be processed on the basis of the determination criterion. For example, the determination unit 15c determines the identity for the operation event to be processed by using the extracted attribute value. That is, the determination unit 15c determines the identity for the operation event to be processed by matching an operation event including the character string or an operation event satisfying the numerical range by using the first determination criterion. Further, the determination unit 15c determines the identity for the operation event to be processed by matching a result of adoption of the condition set for each of the attribute elements by using the second determination criterion.
Describing using a specific example, in a case where a fact that the attribute element “operation type” exactly matches is estimated as a determination criterion (first determination criterion) in the identical operation set, the determination unit 15c estimates the fact that the “operation type” exactly matches as a condition for determining the identity of the operation events. Further, in a case where an operation event in which the attribute element “operation type” exactly matches is estimated as a final determination criterion as a determination criterion (second determination criterion) between the identical operation sets, the determination unit 15c searches for an operation event that exactly matches the attribute element “operation type” from operation events not connected by the user, and outputs the found operation event as a determination result. Note that the determination processing described above will also be described in detail in [Details of each of pieces of processing] (5. Operation event determination processing) described later.
In addition, the determination unit 15c transmits the output determination result to the output unit 12. Note that the determination unit 15c may store the output determination result in the storage unit 14.
In addition, the determination unit 15c determines the identity for the operation event to be processed by presenting the determination result obtained by determining the identity to the user and outputting the determination result approved by the user.
Describing using a specific example, in a case where operation events in which the attribute element “operation type” exactly matches are output as the identical operation events in a plurality of visual images, the determination unit 15c outputs again an operation event of which the visual image is selected by the click operation by the user as a confirmed determination result. Note that the estimation processing described above will also be described in detail in [Details of each of pieces of processing] (6. Determination processing by interaction with user) described later.
[Details of Each of Pieces of Processing]
Details of each of pieces of processing according to the present embodiment will be described by using
Processing of receiving exemplification by connection of operation events will be described with reference to
First, the user is caused to exemplify one or more combinations of the identical operations. For example, as illustrated in
Then, the determination device 10 receives operation events connected with each other by the user as the user's exemplification. In
(2. Rule Type for Each Attribute Value)
The rule type for each attribute value will be described with reference to
The determination device 10 applies the following four types of rules also illustrated in
As illustrated in
(3. Details of Rule for Each Attribute Value)
Prior to the rule estimation processing, details of the rule for each attribute value will be described. Hereinafter, description will be given of a character string determined by an exact match (rule details 1), a character string determined by a partial match (rule details 2), and an item determined by a numerical range (rule details 3) in this order.
(Rule details 1: Character String Determined By Exact Match)
First, details of a rule for determining a character string by an exact match (rule type A) will be described. Hereinafter, description will be given in the order of rule estimation processing 1 to which the rule type A is applied (first stage), rule estimation processing 2 to which the rule type A is applied (second stage), and rule matching processing.
(Rule Estimation Processing 1: Estimation Processing in Identical Operation Set)
In a case where all the attribute values exactly match in the exemplified identical operation set, the determination device 10 adopts the present rule for the corresponding attribute element. On the other hand, in a case where the attribute values do not exactly match in the exemplified identical operation set, the determination device 10 rejects the present rule for the corresponding attribute element. Note that, also in a case where all the attribute values are “null” in the exemplified identical operation set, the present rule is adopted for the corresponding attribute element.
(Rule Estimation Processing 2: Estimation Processing Between Identical Operation Sets)
In a relationship between a plurality of identical operation sets, if there is a rejected identical operation set, the determination device 10 rejects the identical operation sets as a whole.
In a case where corresponding attribute values exactly match between operation events to be compared, the determination device 10 determines that the present rule is a match (matched). In addition, in a case where it is not necessary to distinguish between upper case and lower case, the determination device 10 performs comparison using a value obtained by converting the corresponding attribute values into upper case or lower case.
(Rule Details 2: Character String Determined By Partial Match)
Second, details of a rule for determining a character string by a partial match (rule type B) will be described. Hereinafter, description will be given in the order of rule estimation processing 1 to which the rule type B is applied (first stage), rule estimation processing 2 to which the rule type B is applied (second stage), and rule matching processing.
(Rule Estimation Processing 1: Estimation Processing in Identical Operation Set)
In a case where “null” is included in the corresponding attribute value in the exemplified identical operation set, the determination device 10 rejects the present rule for the corresponding attribute element. On the other hand, the determination device 10 finds the longest common partial character string in the exemplified identical operation set. At this time, a ratio of the length of the common partial character string to the length of the attribute value with the maximum number of characters in the exemplified identical operation set is obtained as a lowest matching ratio (matching rate), and this lowest matching ratio is used as a parameter of the present rule. Then, in a case where the lowest matching ratio is less than or equal to a threshold, the determination device 10 rejects the present rule.
Note that the above threshold can be arbitrarily set, but for example, it is sufficient that the rule is rejected in a case where the ratio is less than or equal to 50%. In addition, to perform more advanced processing, information regarding true/false of “forward match”, “backward match”, “partial match”, and “exact match” may be considered, a plurality of common parts may be considered, or a character string length may be considered.
Among the plurality of operation event sets to be compared, if there is a rejected identical operation set, the determination device 10 rejects the operation event sets as a whole. In addition, the determination device 10 sets the minimum lowest matching ratio among the plurality of operation event sets to be compared as a parameter of the whole.
In a case where a ratio of the longest common partial character string of the corresponding attribute value exceeds the lowest matching ratio between the operation events to be compared, the determination device 10 determines that the present rule is a match (matched). In addition, in a case where it is not necessary to distinguish between upper case and lower case, the determination device 10 performs comparison using a value obtained by converting the corresponding attribute values into upper case or lower case.
Third, details of a rule for determination by a numerical range (rule type C) will be described. Hereinafter, description will be given in the order of rule estimation processing 1 to which the rule type C is applied (first stage), rule estimation processing 2 to which the rule type C is applied (second stage), and rule matching processing.
(Rule estimation Processing 1: Estimation Processing in Identical Operation Set)
In the exemplified identical operation set, “in a case where null is included in the corresponding attribute value”, “in a case where a value that cannot be handled as a numerical value is included in the corresponding attribute value”, or “in a case where another abnormal value is included in the corresponding attribute value (example: width is a negative value)”, the determination device 10 rejects the present rule for the corresponding attribute element.
In addition, the determination device 10 calculates a standard deviation σ in the exemplified identical operation set, and uses the standard deviation o as a parameter of the present rule. At this time, the determination device 10 may reject the present rule in a case where the standard deviation σ is greater than or equal to a certain threshold or in a case where a sufficient number of operations are not exemplified (only one operation is exemplified). For example, in a case where the threshold is set to 30, and in a case where the standard deviation σ is greater than or equal to 30, it is regarded that the variation is large and there is almost no commonality, and the rule is rejected.
Among the plurality of operation event sets to be compared, if there is a rejected identical operation set, the determination device 10 rejects the operation event sets as a whole. In addition, the determination device 10 sets the maximum standard deviation o among the plurality of operation event sets to be compared as a parameter of the whole.
In a case where the corresponding attribute value falls within a range of (an absolute value of a difference between values of two attribute elements)≤2 kσ between the operation events to be compared, the determination device 10 determines that the present rule is a match (matched). Here, k is a constant and is arbitrarily determined. In addition, in a case where it is assumed that variation of values follows a normal distribution, k=3 (range of 99.7%) is generally preferable.
Details of processing of estimating the rule for each attribute value will be described with reference to
As the estimation processing at the first stage, rule estimation in the exemplified identical operation set will be described. First, the determination device 10 determines “adopted” or “rejected” for each attribute element in accordance with a rule type set in advance for each attribute element. Next, the determination device 10 extracts a parameter from an attribute value of an attribute element determined as “adopted” in accordance with the rule type set in advance for each attribute element. Then, the determination device 10 estimates whether it is “adopted” or “rejected”, or the extracted parameter for each attribute element as a rule (first determination criterion) corresponding to the attribute element.
In the example in the upper part of
In addition, in the examples in the upper and lower parts of
As the estimation processing at the second stage, processing of confirming consistency between a plurality of exemplified identical operation sets will be described. First, the determination device 10 compares determinations whether it is “adopted” or “rejected” of respective attribute elements in the plurality of identical operation sets. At this time, among the plurality of identical operation sets to be compared, if there is a rejected identical operation set, the determination device 10 rejects the identical operation sets as a whole. Then, the determination device 10 estimates a pattern of “adopted” or “rejected” of each matched attribute element as a rule (second determination criterion). That is, the estimation processing at the second stage can be said to be processing of finding a rule as to which attribute value is common in the operations included in the identical operation set.
In the example of
Details of processing of determining identical operation events from the estimated rule will be described with reference to
In the example of
In addition, the determination device 10 may use a rule (example: a parameter of each attribute element) in the operation event set estimated from an exemplified operation event set to determine the identity for an operation event that is not exemplified, and output identical operation events that are not exemplified.
(6. Determination Processing by Interaction with User)
Hereinafter, details of processing of determining an operation event by interaction with the user will be described. In some cases, the determination device 10 cannot correctly determine the identity of the operation events, such as a case where the number of the exemplified operation events described above is small or a case where variety of the exemplified operation events is insufficient. For that reason, instead of immediately confirming the determination result, the determination device 10 can temporarily indicate a determined operation event to the user, and confirm the determination result after confirmation from the user. That is, in a case where the presented determination result is determined to be inappropriate by the user, the determination device 10 can also prompt the user to cancel the temporary determination result once and increase the number of exemplifications.
By gradually increasing the number of exemplifications by such interactive exchange, it is possible to cause the user to more efficiently exemplify operation events. Further, by providing a user interface (UI) that allows ON/OFF of various set thresholds and rules adopted by estimation, it is also possible to respond more advanced user requirements.
A flow of each of pieces of processing according to the present embodiment will be described in detail with reference to
First, the reception unit 15a of the determination device 10 executes operation event selection reception processing (step S101). Next, the estimation unit 15b of the determination device 10 executes determination rule estimation processing (step S102). Then, the determination unit 15c of the determination device 10 executes operation event determination processing (step S103), and ends the processing. Note that the following steps S101 to S103 can be executed in different orders. In addition, there may be omitted processing among the following steps S101 to S103.
First, the operation-event selection reception processing by the reception unit 15a will be described. In this processing, the user is caused to exemplify one or more combinations of identical operation events, and operation logs of the exemplified identical operation events are received. At this time, by visually displaying the operation events chronologically and causing the user to select a connection, the user can recognize which operation each operation event specifically is without understanding a content of an attribute value recorded in the operation log.
Second, the determination rule estimation processing by the estimation unit 15b will be described. In this processing, in accordance with a rule type set in advance for each attribute element of the operation event for which selection is received, “adopted” or “rejected” is determined for each attribute element, a parameter is extracted from an attribute value of the attribute element determined as “adopted”, and the extracted parameter is estimated as a rule corresponding to the attribute element. At this time, by connecting the attribute element with the rule type to be used in advance, it is possible to effectively estimate a determination rule of the selected operation event. In addition, in this processing, a rule for the user to determine identity can also be estimated from the pattern of “adopted” or “rejected” of each attribute element, and identical operation events can be estimated in addition to the exemplified operation events.
Third, the determination rule estimation processing by the determination unit 15c will be described. In this processing, the estimated determination rule is used to check the rule for operation events other than the exemplified operation events, and identical operation events are determined. At this time, by temporarily indicating the determined operation event to the user instead of immediately confirming the determination result, and confirming the determination result of the identical operation events after confirmation from the user, it is possible to prompt the user to gradually increase the number of exemplifications by interactive exchange, and it is possible to easily and effectively determine the identical operation events.
First, in the determination processing according to the present embodiment described above, operation events are received, a determination criterion is estimated for determining the identity of the operation events on the basis of an attribute value of an operation log included in the operation events, and the identity is determined for the operation event to be processed on the basis of the estimated determination criterion, and for this reason, in the present processing, identical operation events can be easily connected with each other in pre-processing for process mining.
Here, the process mining will be described. In the process mining, as illustrated in
In such process mining, as illustrated in
Conventionally, such pre-processing is performed manually. For example, when such pre-processing is manually performed, as illustrated in
As described above, since there is no relationship between appearance in the screen and an internal structure (such as a method of assigning an ID), the internal structure cannot be estimated from similarity in appearance that can be determined by a general user. Since there are various internal structures in the screen, the best determination cannot always be made by a fixed algorithm. A user having specialized knowledge can cope with various screen structures by estimating a rule from a tendency of the operation log and constructing an algorithm, but it is difficult for a general user.
For this reason, in a case where division of the operation log in units of cases is manually performed, it is necessary for a worker to understand an internal structure of a system and a meaning of an attribute value of the operation log, and further, it requires a large operation to handle a large amount of logs, and in addition, in a fixed rule algorithm, systems have different internal structures, so that there has been a problem that it is difficult to automatically divide the operation log in units of cases. On the other hand, in the determination processing according to the present embodiment, the identical operation events can be easily connected with each other in the pre-processing for the process mining. In addition, effects that can be achieved by the determination processing according to the present embodiment will be further described below.
In the determination processing according to the present embodiment described above, among images of a plurality of operation events, images of operation events associated with each other by the user as identical operations are received, the determination criterion is estimated by extracting the common attribute value of the operation log, and the identity is determined for the operation event to be processed by using the extracted attribute value. For this reason, in the present processing, in the pre-processing for the process mining, the identical operation events can be easily connected with each other by using the common attribute value of the operation log on the basis of the operation of the image.
In the determination processing according to the present embodiment described above, among captured images of a plurality of operation events displayed in chronological order, a combination of the captured images associated with each other by the user as identical operations is received, the first determination criterion in a set of the operation events associated with each other as identical operations is estimated by extracting a character string or a numerical range commonly included in attribute elements in accordance with a condition set for each of the attribute elements, and the identity is determined for the operation event to be processed by matching an operation event including the character string or an operation event satisfying the numerical range by using the first determination criterion. For this reason, in the present processing, in the pre-processing for the process mining, the identical operation events can be easily connected with each other by using the common attribute value of the operation log on the basis of the operation of the image in accordance with the condition set for each of the attribute elements.
In the determination processing according to the present embodiment described above, the second determination criterion between sets of the operation events associated with each other as identical operations is further estimated by performing comparison of the first determination criterion, and the identity is determined for the operation event to be processed by matching a result of adoption of the condition set for each of the attribute elements by using the second determination criterion. For this reason, in the present processing, in the pre-processing for the process mining, a plurality of identical operation event sets can be easily connected with each other by using the common attribute value of the operation log on the basis of the operation of the image in accordance with the condition set for each of the attribute elements.
In the determination processing according to the present embodiment described above, the identity is determined for the operation event to be processed by presenting the determination result obtained by determining the identity to the user and outputting the determination result approved by the user. For this reason, in the present processing, in the pre-processing for the process mining, the identical operation events can be easily and more effectively connected with each other.
Each component of each device that has been illustrated according to the embodiment described above is functionally conceptual and does not necessarily have to be physically configured as illustrated. In other words, a specific form of distribution and integration of individual devices is not limited to the illustrated form, and all or part of the configuration can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, and the like. Further, all or some of the processing functions performed in each device can be implemented by a CPU and a program to be analyzed and executed by the CPU or can be implemented as hardware by wired logic.
In addition, among the pieces of processing described in the embodiment described above, all or part of the processing described as being automatically performed can be manually performed, or all or part of the processing described as being manually performed can be automatically performed by a known method. The processing procedure, the control procedure, the specific name, and the information including various types of data and parameters that are illustrated in the literatures and the drawings can be freely changed unless otherwise specified.
In addition, it is also possible to create a program in which the processing executed by the determination device 10 described in the above embodiment is described in a language that can be executed by a computer. In this case, the computer executes the program, and thus the advantageous effects similar to those of the above-described embodiment can be obtained. Further, processing similar to that of the foregoing embodiment may be implemented by recording the program on a computer-readable recording medium and reading and executing the program recorded in the recording medium.
As illustrated in
Here, as illustrated in
In addition, various data described in the embodiment described above is stored as program data in, for example, the memory 1010 and the hard disk drive 1090. Then, the CPU 1020 reads the program module 1093 and the program data 1094 stored in the memory 1010 and the hard disk drive 1090 to the RAM 1012 as necessary and executes various processing procedures.
Note that the program module 1093 and the program data 1094 related to the program are not limited to being stored in the hard disk drive 1090 and may be stored in, for example, a removable storage medium and may be read by the CPU 1020 via a disk drive, or the like. Alternatively, the program module 1093 and the program data 1094 related to the program may be stored in another computer connected via a network (such as a local area network (LAN) or a wide area network (WAN)) and may be read by the CPU 1020 via the network interface 1070.
The embodiment described above and modifications thereof are included in the inventions recited in the claims and the equivalent scope thereof, similarly to being included in the technique disclosed in the present application.
10 determination device
11 input unit
12 output unit
13 communication unit
14 storage unit
15 control unit
15
a reception unit
15
b estimation unit
15
c determination unit
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/JP2021/022417 | 6/11/2021 | WO |
