Business Process Estimation Device and Method

Abstract

To provide a business process estimation device and a method that can more accurately estimate a business process.SOLUTION: A business process estimation device 10 comprises: a sample material database 101 that stores a plurality of sample materials; a sample material-task related database 102 that associates a task representation representing tasks with each of the sample materials; a similarity evaluation unit 105 that determines, as a similar sample material, one sample material most similar to intermediate products generated in relation to the sample materials; an access log acquisition unit 106 that acquires an access log representing a date and time of an access to each of the intermediate products; a related task acquisition unit 107 that acquires, for each of the intermediate products, a task representation associated with a corresponding similar sample material as a related task representation; and a business process estimation unit 110 that, on the basis of, the access log and the related task representation, estimates a business process representation representing an order between the task representations.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a business process estimation apparatus and method. For example, it relates to a technique for analyzing the order in which various operations are performed in various operations (hereinafter sometimes simply referred to as "business process"). Also, for example, it relates to a technique for acquiring the execution history of operations (for example, represented in the form of an event log described in this specification) and estimating the business process from this execution history.

Background Art

[0002] As an effort to achieve business efficiency and productivity improvement, DX (Digital Transformation) represented by the introduction of "RPA (Robotic Process Automation)" has attracted attention. RPA is software that substitutes or replaces tasks that have hitherto been handled only by humans or more advanced tasks by utilizing AI, machine learning, etc. DX is for a company to utilize digital technology and transform its organization and business model. In such DX efforts, in order to identify inefficient operations to be improved or transformed, visualization of business processes as shown in Patent Document 1, for example, has been carried out.

[0003] However, regarding the identification of this business process, it has required a great deal of time and effort, such as an expert with business analysis skills observing an organization where operations are being performed, conducting interviews with the operation staff, reading and interpreting operation manuals and standards, manually writing them up, and further repeating the confirmation and correction of the written-up content with various stakeholders related to the operations. Also, depending on the business understanding of the interviewees, infrequent exceptional operations may be overlooked. Furthermore, the more advanced the operation, the more the way of proceeding with the operation continues to change day by day. For this reason, it is not the end to identify the business process at a certain point in time, and it is necessary to keep up with the changes.

[0004] Therefore, in recent years, process mining has attracted attention as a technology for automating the extraction of business processes. This is a technology / method for estimating the tasks being performed in a business and the order of their execution (business process) from the logs (operation history = event logs) in the IT systems used when conducting business, as shown in, for example, Patent Document 2 and Non-Patent Document 1. Note that a task is an element that constitutes a business process. For example, in the procurement business process, there are tasks such as "create a purchase specification" and "check inventory", and in the design business process, there are tasks such as "design the shape of part XX", "evaluate the strength of part XX", and "create materials for design review". With this process mining technology, it is possible to automate or streamline business analysis that conventionally had to be performed by experts, and by continuously using it, changes in the business process can also be captured.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Patent Document 2

Non-Patent Documents

[0006]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0007] However, the above technology has the following problems.

[0008] In Patent Document 1, it is necessary for an expert to identify business processes. In the technologies described in Patent Document 2 and Non-Patent Document 1, it is necessary to generate and obtain event logs corresponding to all tasks that make up a business process in an IT system.

[0009] For example, in a travel expense and expense settlement system, a purchase order management system for order management based on inventory information, etc., all tasks to be performed must be functions of the system and must be recordable as event logs. This is because if the overall picture of the business process is not recorded in the event log, the information will be fragmented.

[0010] Also, the functions in an IT system and the tasks that make up a business process must correspond one-to-one. For example, tasks such as "check the specification", "create a quotation", and "approve the quotation" in the purchase order business are implemented as functions of the purchase order system and can correspond one-to-one. On the other hand, in the design business of hardware products, tasks such as "design the shape of the housing parts", "design the shape of the motor parts", and "design the component layout of the entire product" use a CAD system, but the functions of the CAD system and the tasks do not correspond one-to-one. Similarly, there are many functions in spreadsheet software, and tasks such as "evaluate the strength of the housing parts" and "estimate the cost of the motor parts" are performed using these functions. In this case as well, it is not possible to take a one-to-one correspondence between the functions and the tasks.

[0011] Therefore, for businesses where the tasks that make up the business process and the functions of the IT system do not correspond, the problem is that it cannot be applied. In routine business, since the introduction and efficiency improvement of IT systems are progressing, tasks and functions often correspond. On the other hand, in non-routine business such as product planning, structural design, and production preparation, since the functions of the IT system do not correspond one-to-one with all tasks, many tasks will be missed from the event log, and as a result, the business process estimated through process mining will be incomplete.

[0012] The present invention has been made in view of the above circumstances, and an object thereof is to enable more accurate estimation of business processes.

Means for Solving the Problems

[0013] An example of a business process estimation apparatus according to the present invention is a sample data database that stores a plurality of sample materials, a sample material-task association database that associates a task expression representing a task with each of the sample materials, a similarity evaluation unit that determines, for each intermediate work product generated in association with any of the sample materials, one of the sample materials that is most similar to the intermediate work product as a similar sample material, an access log acquisition unit that acquires an access log representing the date and time of access to each of the intermediate work products, a related task acquisition unit that acquires, for each of the intermediate work products, the task expression associated with the corresponding similar sample material as a related task expression, a business process estimation unit that estimates a business process expression representing the order between the task expressions based on the access log and the related task expression, and includes.

[0014] An example of a business process estimation method according to the present invention is a business process estimation method executed by a computer, a step of associating a task expression representing a task with each of a plurality of sample materials, and a step of determining, for each intermediate work product generated in association with any of the sample materials, one of the sample materials that is most similar to the intermediate work product as a similar sample material, a step of acquiring an access log representing the date and time of access to each of the intermediate work products, For each of the intermediate work products, obtaining, as associated task expressions, the task expressions associated with the corresponding similar sample materials; estimating a business process expression representing an order between the task expressions based on the access log and the associated task expressions; comprising.

Advantages of the Invention

[0015] According to the business process estimation apparatus and method of the present invention, a business process can be estimated more accurately.

[0016] For example, even when the tasks constituting the business process do not correspond one-to-one with the functions of the IT system, an event log can be automatically generated, so the applicable range of process mining technology is expanded. Therefore, it is possible to more accurately automate or streamline the business analysis that conventionally had to be performed by experts.

[0017] In addition, by continuously using the business process estimation apparatus and method according to the present invention, changes in the business process can also be captured.

Brief Description of the Drawings

[0018]

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Best Mode for Carrying Out the Invention

[0019] Hereinafter, an example of the business process estimation apparatus of the present invention will be described with reference to the drawings.

Example

[0020] FIG. 1 is a configuration diagram showing an embodiment of a business process estimation apparatus 10 according to the present invention. FIG. 1(a) shows an example of a hardware configuration, and FIG. 1(b) shows an example of a functional flow. The business process estimation apparatus 10 implements the business process estimation method described in this embodiment.

[0021] As shown in FIG. 1(a), the business process estimation apparatus 10 can be configured using a computer having a known hardware configuration, and includes, for example, an arithmetic means 11 and a storage means 12. The arithmetic means 11 includes, for example, a processor, and the storage means 12 includes a storage medium such as a semiconductor memory device and a magnetic disk device. Part or all of the storage medium may be a non-transitory storage medium.

[0022] Further, the computer may include input / output means. The input / output means includes, for example, an input device such as a keyboard and a mouse, an output device such as a display and a printer (for example, an output device 100 described later in relation to FIG. 1(b)), and a communication device such as a network interface.

[0023] The storage means may store a program. By the processor executing this program, the computer may execute the functions described in this embodiment.

[0024] The business process estimation device 10 shown in Fig. 1(a) has each function represented by the functional blocks shown in Fig. 1(b). For example, the business process estimation device 10 includes a sample data database 101 that stores a plurality of sample materials used in the business, and a sample material - task association database 102 that associates an expression representing a task (task expression) with each of the sample materials. The task corresponds to or is related to the work of creating intermediate deliverables.

[0025] In addition, the business process estimation device 10 includes a document similarity evaluation unit 105 (similarity evaluation unit) that searches for the sample material most similar to the intermediate deliverable file 103 created as an intermediate deliverable during business execution and registers it as the similar sample material 104, an access log acquisition unit 106 that acquires the access log for the intermediate deliverable file 103, a related task acquisition unit 107 that acquires the task expression related to the similar sample material 104 from the sample material - task association database 102, an event log generation unit 108 that creates an event log from the intermediate deliverable access log and the related task expression, a business process estimation unit 110 that estimates the business process from the event log and estimates the business process data 109, and a business process visualization unit 111 that outputs (for example, displays) the business process data 109 to the output device 100.

[0026] Also, in a modification example, it is also possible to generate sample materials from a plurality of past intermediate deliverables and automatically add them to the sample material database 101.

[0027] Fig. 2 is a functional flowchart of a business process estimation device 20 having a sample material automatic generation function according to such a modification example. The business process estimation device 20 includes an intermediate deliverable similarity calculation unit 201 that calculates the similarity between a plurality of intermediate deliverable files 103 created in past business, and an intermediate deliverable clustering unit 202 that clusters the intermediate deliverables based on the similarity and adds a representative intermediate deliverable to the sample material database 101 for each cluster.

[0028] An example of each means and database according to Example 1 or its modified example will be described below.

[0029] (1) Specimen data database 101 and intermediate result file 103 The specimen data database 101 is a database that stores specimen data in the materials used in business. Specimen data is, for example, something in which the characteristics of the content in the intermediate result are expressed (in taxonomy, which is a field of biology, a specimen is defined as "evidence for proving its existence and clarifying its characteristics", and this definition is based on it). Specimen data is, for example, in the form of a data file handled by a computer. However, the specimen data is not limited to the data that meets such a definition, and any content and form of data can be used as the specimen data.

[0030] The intermediate result file 103 is a database that stores intermediate results generated in relation to any of the specimen data. Examples of intermediate results include, in the development and design stages, intermediate results such as reports, specifications, deliberation documents, technical materials, drawings, etc. To give a more specific example, there are functional specifications, experimental reports, technical materials that record assumed problems and countermeasures, etc. Also, in the case of data related to calculations such as strength, heat load, cost, etc., they are files such as spreadsheet software or simulation software created in past projects. Also, it may be a file including 2D drawings or 3D CAD data showing shapes and structures, component assembly information, various attribute information (material, component type, welding instruction, etc.).

[0031] As another example of intermediate results, in the production stage, there are die data, manufacturing process sheets, assembly process sheets, quality plans, inspection records, cost estimates, etc. In addition, all things created in the process of a certain business, such as program codes, meeting minutes, test data, operation manuals, etc., can be used as intermediate results.

[0032] In business, when creating this intermediate work product, it is rare to create it from scratch. Generally, it is created based on past similar intermediate work products, or template materials and sample materials prepared in advance. It is preferable to use such past intermediate work products, template materials, and sample materials as the base as sample materials. A collection of such sample materials can be used as the sample material database 101.

[0033] An example of the table structure of the sample material database 101 is shown in FIG. 3. In this example, it has four fields: ID, sample material name, storage address of the file that is the entity of the sample material, and file type.

[0034] (2) Sample Material - Task Related Database 102 The sample material - task related database 102 is a database in which associations of tasks are registered for the sample materials registered in the sample material database 101 when creating intermediate work products based on those sample materials. For example, for a sample material named "Strength Analysis Results Report", a task expression such as "Perform strength analysis" can be associated, and for a sample material named "Assembly Cost Estimate", a task expression such as "Estimate assembly cost" can be associated.

[0035] Note that this task expression is used, for example, for display in the business process expression (FIG. 9, etc.) described later. The specific expression can be any expression as long as the user who views the business process expression can identify the task, and there is no particular limitation. However, it is preferable that the task name is represented by text data as shown in the figure because the processing becomes simple.

[0036] An example of the table structure of the sample material - task related database 102 and its data is shown in FIG. 4. In this example, it has three fields: ID, sample material name, and task name (task expression).

[0037] (3) Document Similarity Evaluation Unit 105 During the execution of operations, the Document Similarity Evaluation Unit 105 searches for the most similar sample document from the Sample Document Database 101 for the intermediate deliverable file 103 created during the operation, and registers it as the similar sample document 104. That is, for each of the intermediate deliverables, one sample document that is most similar to the intermediate deliverable among the sample documents is determined as the similar sample document and associated with the intermediate deliverable.

[0038] The similarity index can be appropriately defined by those skilled in the art. Known similarity evaluation techniques may be used. For example, when the intermediate deliverable and the sample document are documents, each document is vectorized by some method, the similarity between the vectors is calculated, and the sample document with the highest similarity can be set as the similar sample document 104. Here, various methods have been proposed for the document vectorization method and the similarity calculation method, but any method can be used. It is only necessary to be able to calculate the similarity between documents, and the method does not matter.

[0039] Note that the intermediate deliverable and the sample document do not have to be documents, and for example, image data, spreadsheet data, or 3D shape data may be used. Regarding images and 3D data as well, various methods for vectorization and calculation of the similarity between vectors have been proposed, and various types of the content of the data can be used.

[0040] An example of a method for vectorization and similarity calculation in a text document is shown below. For a text document, morphological analysis is used to segment it into words. Note that this morphological analysis may be omitted in the case of languages where words such as English are separated by spaces. Next, the number of occurrences of each word is counted and represented as a vector. For the vectors created for two documents, the cosine similarity is calculated (Reference: Eiji Nanba, "Measurement of Similarity between Texts", Information Science and Technology, 2020, Vol. 70, No. 7, pp. 373-375). In this example, the similarity is calculated based on the word occurrence frequency, but other methods for evaluating the importance of words called TF-IDF may also be used (Reference: Akihiro Kageyama, Hiroshi Tsuji, "Feature Extraction Method for Research Institutions Using TF / IDF Algorithm", Transactions of the Institute of Electrical Engineers of Japan, Part C (Journal of Electronics, Information and Systems), 2005, Vol. 125, No. 5, pp. 713-719).

[0041] Similarly, an example of a method for similarity calculation in 3D shape data is shown below. The target shape is represented in a voxel structure, blocks are defined by a plurality of adjacent voxels, spectra are calculated for each block, and the spectra are represented as vectors (Reference: Specification of Patent No. 5024767). For the vectors created for two 3D shape data in the same way as in the case of documents, the cosine similarity is calculated.

[0042] (4) Access Log Acquisition Unit 106 The access log acquisition unit 106 acquires the access log of the intermediate product file 103. In this embodiment, the access log represents the date and time of access to each intermediate product, and targets, for example, access for creation and access for editing (updating). The date and time of access are represented, for example, by a timestamp. (5) Related Task Acquisition Unit 107 The related task acquisition unit 107 acquires the task expression related to the similar sample material 104 from the sample material-task related database 102. In particular, for each intermediate product, the task expression associated with the corresponding similar sample material is acquired as the related task expression for that intermediate product.

[0043] For the sample data - task - related database 102 shown as an example in FIG. 4, if a sample data named "Operation Condition Definition Document" was registered as the similar sample data 104 of a certain intermediate work product, the related task expression related to that intermediate work product would be "Determine the operation conditions".

[0044] (6) Event log generation unit 108 The event log generation unit 108 creates an event log based on the access log of the intermediate work product and the related task expression. The event log has, for example, the table structure and data shown in FIG. 5. In this example, it has a table structure with five fields: ID, project name, task name (related task expression), timestamp, and person in charge (access executor).

[0045] Note that for the project name, in this example, it is automatically determined for each intermediate work product. For example, if the storage location (folder name, etc.) of the intermediate work product contains the project name according to a predetermined naming rule, the event log generation unit 108 can obtain the project name based on the storage location of the intermediate work product. Also, if there is data associating the person in charge with the project name (for example, data indicating the project names that each person in charge is engaged in and the periods during which they are engaged in those projects), the event log generation unit 108 can obtain the project name based on that data. The method of obtaining the project name can be arbitrarily designed. The business process estimation device 10 or 20 may separately have functional means for accepting the designation of the project name or automatically specifying it.

[0046] As an example of more specific operations, the event log generation unit 108 obtains the project name for each intermediate work product and generates an event log based on the project name, the access log, and the related task expression. As shown in FIG. 5, the event log associates the project name, the date and time of access, and the task expression for that intermediate work product.

[0047] (7) Business process estimation unit 110 and business process data 109 The business process estimation unit 110 estimates a business process representation (for example, FIG. 9 described later) based on the event log. The business process representation is a representation by a model that represents a business process in a specific representation format and is a representation that represents the order between task representations. The type of representation format can be arbitrarily designed. The business process data 109 is specific data corresponding to the business process representation.

[0048] Note that since the event log is generated based on the access log and the related task representation as described above, it can also be said that the business process estimation unit 110 estimates the business process representation based on the access log and the related task representation.

[0049] The method of estimating the business process from the event log can be arbitrarily designed, and known methods may be used. An example of a typical method will be described below.

[0050] [Step 1] Arrange the tasks in the order in which they were performed for each case. For example, for each case name, arrange the related task representations for each intermediate work product in the order in which access was made to the intermediate work product.

[0051] As a specific example, consider the following access. The alphabet is the related task representation for the intermediate work product to which access was made. The expression (A, B, C) indicates that access was made in the order of A → B → C. Case 1: (A, B, C, D) Case 2: (A, C, D) Case 3: (A, E, C, D) Case 4: (A, B, C, E, C, D)

[0052] [Step 2] Extract the task transitions for all cases.

[0053] For example, looking only at Project 1, the business process representation can be expressed as a task transition diagram like 601 in FIG. 6. Next, when adding the transition pattern of Project 2, the order in which C appears after A is added, so it can be expressed as 602 in FIG. 6. Similarly, when adding the transition pattern of Project 3, the order in which E appears after A and the order in which C appears after E are added, so it can be expressed as 603 in FIG. 6. Furthermore, when adding the transition pattern of Project 4, the order in which E appears after C is added, so it can be expressed as 604 in FIG. 6.

[0054] In this way, the model representing the task transition is registered in the business process data 109 as the business process representation. The model (representation format) representing the task transition can be arbitrarily designed, and known technologies may be used. For example, BPMN (Business Process Model and Notification), Petri net, UML activity diagram, etc. have been proposed, and it is advisable to register in an appropriate format.

[0055] (8) Intermediate work product similarity calculation unit 201 The intermediate work product similarity calculation unit 201 calculates the similarity between a plurality of intermediate work product files 103 created in past operations. Here, the method for calculating the similarity between each other can be, for example, the same as that of the document similarity evaluation unit 105.

[0056] (9) Intermediate work product clustering unit 202 The intermediate work product clustering unit 202 clusters the intermediate work products based on the similarity calculated by the intermediate work product similarity calculation unit 201, and determines a representative intermediate work product (representative intermediate work product) for each cluster. Then, this representative intermediate work product is stored in the sample data database 101 as sample data.

[0057] Regarding the clustering method, there is no particular limitation, but for example, the K-means method, the shortest distance method, the multidimensional scaling method, the Ward method, etc. can be considered for adoption.

[0058] Thus, according to the modification example (Fig. 2) including the intermediate work product similarity calculation unit 201 and the intermediate work product clustering unit 202, since the sample data is automatically added, the labor of adding the sample data can be omitted. Note that the task name (task expression) corresponding to the automatically added sample data may be configured such that a human inputs it to the business process estimation device 20 in a timely manner, or may be configured such that the business process estimation device 20 automatically determines it based on the content of the sample data.

[0059] Subsequently, an example of the processing procedure and data flow using this device will be described with reference to Figs. 7 to 9. The processing procedure proceeds, for example, according to the function flowcharts of Figs. 1 and 2.

[0060] In this example, assume that the data shown in Fig. 3 is registered in the sample data database 101, the data shown in Fig. 4 is registered in the sample data - task related database 102, and the data shown in Fig. 7 is registered as the intermediate work product file 103.

[0061] First, the document similarity evaluation unit 105 searches the sample data database 101 for the most similar sample data with respect to the intermediate work product file 103 and registers it as the similar sample data 104. In this example, assume that the similar sample data 104 is determined as shown in Fig. 8 with respect to the intermediate work product file 103 shown in Fig. 7.

[0062] Next, the access log acquisition unit 106 acquires the access log of the intermediate work product file 103. Subsequently, the related task acquisition unit 107 acquires the task expression related to the similar sample data 104 from the sample data - task related database 102. Subsequently, the event log generation unit 108 creates an event log from the intermediate work product access log and the related task. In this example, the event log shown in Fig. 5 is created.

[0063] For this event log, the business process estimation unit 110 estimates the business process and registers it as business process data 109. As a result, the business process representation shown in FIG. 9 is estimated. The business process visualization unit 111 visualizes the business process representation (for example, displays it on a display device).

[0064] As an example, pay attention to the task representation of "select device configuration". In the event log of FIG. 5, as the access with ID 2, there is an access related to the project name "Company XX", and the next access related to the same project name "Company XX" is "design new" with ID 4. Also, as the access with ID 5, there is an access related to another project name "Company YY", and the next access related to the same project name "Company YY" is "design new" with ID 8. Furthermore, as the access with ID 14, there is an access related to another project name "Company ZZ", and the next access related to the same project name "Company ZZ" is "conduct design review" with ID 15.

[0065] Summarizing this, either "design new" or "conduct design review" will appear after "select device configuration". Such processing is performed for all access logs, and the business process representation shown in FIG. 9 is generated.

[0066] In this embodiment, in the business process representation, the task representation is related to the node. In the example of FIG. 9, the task representation is described in the rectangular node. Also, in this embodiment, the order between the task representations is represented by the link connecting the nodes. In the example of FIG. 9, the order between the nodes is represented by the link with an arrow. By using such a representation, the flow of tasks can be easily visualized.

[0067] In the example of FIG. 9, both the nodes and the links are represented in the image, but it is also possible to represent the nodes and the links in a numerical or other data format.

[0068] In the example of FIG. 9, when there are multiple input links or multiple output links for the same node, they are integrated via a diamond-shaped mark, but such integration processing is not essential.

[0069] As described above, in the business process estimation device 10 or 20 according to this embodiment, when there are multiple accesses to one or more intermediate work products related to the same case name in the event log, the business process estimation unit 110 can estimate the order between task expressions based on the order between the multiple accesses.

[0070] As described above, since the case name is used in this embodiment, even when multiple cases are in progress simultaneously, each case can be distinguished and processed so as not to confuse the business processes of different cases. However, the use of the case name is not essential, and in a modified example, the use of the case name can be omitted.

[0071] In particular, the business process estimation unit 110 can extract pairs consisting of two adjacent accesses to one or more intermediate work products related to the same case name in the event log, and estimate the order between task expressions based on the order of accesses in each pair.

[0072] As described above, by estimating the order in units of pairs consisting of only two accesses, the structure of the business process expression becomes simple and the visibility can be improved. However, in a modified example, it is also possible to estimate the order between task expressions based on a set including three or more consecutive accesses.

[0073] Note that in this embodiment, as shown in FIG. 9, the finally generated business process expression does not include the case name (such as "Company XX"). Therefore, it can be a highly general-purpose business process expression not limited to a specific case. However, in a modified example, it can also include the case name.

[0074] As described above, according to the business process estimation device 10 or 20 according to this embodiment, the business process can be estimated more accurately. For example, even when the tasks constituting the business process do not correspond to the functions of the IT system, an event log can be automatically generated, so the applicable range of process mining is expanded. For this reason, it is possible to automate or streamline the business analysis that conventionally had to be performed by experts, and changes in the business process can also be captured by continuous use.

Explanation of Signs

[0075] 10, 20... Business process estimation device 100... Output device 101... Sample data database 102... Sample data - task related database 103... Intermediate result file 104... Similar sample data 105... Document similarity evaluation unit (similarity evaluation unit) 106... Access log acquisition unit 107... Related task acquisition unit 108... Event log generation unit 109... Business process data 110... Business process estimation unit 111... Business process visualization unit 201... Intermediate result similarity calculation unit 202... Intermediate result clustering unit

Claims

1. A specimen data database for storing a plurality of specimen materials, A specimen material-task related database for storing data associating a task expression representing a task with each of the specimen materials, A similarity evaluation unit that, for each of the intermediate products generated in relation to any of the specimen materials, determines, as a similar specimen material, one of the specimen materials that is most similar to the intermediate product among the specimen materials, An access log acquisition unit that acquires an access log representing the date and time of access to each of the intermediate products, A related task acquisition unit that, for each of the intermediate products, acquires, as a related task expression, the task expression associated with the corresponding similar specimen material, A business process estimation unit that estimates a business process expression representing the order between the task expressions according to the access date and time of the intermediate product described in the access log, An event log generation unit that acquires a case name for each of the intermediate products and generates an event log associating the case name, the access date and time, and the task expression based on the case name, the access log, and the related task expression, comprising, The business process estimation unit estimates the business process expression by estimating the order of the task expressions for each case name according to the access date and time of each case name described in the event log. A business process estimation device.

2. In the business process estimation device according to Claim 1, In the business process expression, the task expression is represented by a node, and the order between the task expressions is represented by a link connecting the nodes. A business process estimation device.

3. In the business process estimation device according to Claim 1, When there are multiple accesses to one or more of the intermediate products related to the same case name in the event log, the business process estimation unit estimates that the accesses occurred in the order between the multiple accesses to the task corresponding to the intermediate product, thereby estimating the order between the task expressions. A business process estimation device.

4. In the business process estimation apparatus according to claim 3, the business process estimation unit extracts, from the event log, a pair consisting of two adjacent accesses to one or more of the intermediate work products related to the same case name, and estimates the order between the task expressions based on the order of accesses in each pair. A business process estimation apparatus.

5. In the business process estimation apparatus according to claim 1, A business process estimation apparatus, wherein the business process expression does not include the case name.

6. A business process estimation method executed by a computer, comprising: For each of a plurality of sample materials, associating a task expression representing a task; and for each of the intermediate work products generated in relation to any of the sample materials, determining, as a similar sample material, the one sample material among the sample materials that is most similar to the intermediate work product. Obtaining an access log representing the date and time of access to each of the intermediate work products. For each of the intermediate work products, obtaining, as a related task expression, the task expression associated with the corresponding similar sample material. Estimating a business process expression representing the order between the task expressions according to the access date and time of the intermediate work product described in the access log. Obtaining a case name for each of the intermediate work products, and generating an event log associating the case name, the access date and time, and the task expression based on the case name, the access log, and the related task expression. Comprising: In the step of estimating the business process expression, the business process expression is estimated by estimating the order of the task expressions for each case name according to the access date and time for each case name described in the event log. A business process estimation method.

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