Business process management system and method thereof

Abstract

The present invention provides a business process management system and a business process management system method. The business process management system system includes a storage device and a processor. The storage device stores a data mining module, a path process matching module and a process modeling optimization module. The processor executes multiple modules and obtains an enterprise system operation log. The processor executes the data mining module according to the enterprise system operation log to obtain a frequent path set including multiple event frequent paths. The processor inputs the frequent path set and multiple original business processes into the path process matching module, and executes the path process matching module to generate a matching path set that matches the original business process. The processor executes the process modeling optimization module according to the frequent path set to generate a frequent path graph.

Description

Technical Field

[0001] The present invention relates to a program system, in particular to a business process management system and method thereof. Background Art

[0002] With the development of enterprise systems and the digitization of enterprise processes, the processes between systems and business processes have become more complex and diverse. Therefore, when the system performance of the enterprise system is abnormal or the business process is too time-consuming, it is difficult for managers to find ways to improve and the reasons for poor performance from the complex business processes and system processes. As a result, it is not easy for users or managers to find improvement guidelines and existing process problems from the complicated business processes. Moreover, in the process of complex interactive use between systems, it is difficult for managers to add or develop new business processes on their own. As a result, when the business process efficiency is too low or the manager wants to improve the existing business process, it is difficult to review and analyze the existing business process, resulting in low business efficiency and the inability to improve the business process based on existing operating data. In view of this, several embodiments of the solution will be proposed below. Summary of the invention

[0003] The present invention is directed to a business process management system and method thereof, which can provide operators or managers with reference information and suggestions for optimizing enterprise processes based on enterprise system operation logs and original business processes.

[0004] According to an embodiment of the present invention, the business process management system of the present invention includes a storage device and a processor. The storage device stores multiple modules. The processor is coupled to the storage device. The processor executes multiple modules. The processor obtains an enterprise system operation log, and executes a data mining module according to the enterprise system operation log to obtain a frequent path set including multiple event frequent paths. The processor inputs the frequent path set and multiple original business processes into a path process matching module, and executes the path process matching module to generate a matching path set that matches the original business process. The processor executes a process modeling optimization module according to the frequent path set to generate a frequent path graph.

[0005] According to an embodiment of the present invention, the business process management method of the present invention includes the following steps: obtaining an enterprise system operation log; executing a data mining module based on the enterprise system operation log to obtain a frequent path set including multiple event frequent paths; generating a matching path set that matches the original business process based on the frequent path set and multiple original business processes through a path process matching module; and generating a frequent path graph based on the frequent path set through a process modeling optimization module.

[0006] Based on the above, the business process management system and method of the present invention automatically generates a matching path that matches the original business process and establishes a frequent path diagram for each event information based on the enterprise system operation log and the original business process.

[0007] In order to make the above features and advantages of the present invention more clearly understood, embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 is a schematic diagram of a business process management system according to an embodiment of the present invention;

[0009] Figure 2 is a flow chart of a business process management system method according to an embodiment of the present invention;

[0010] Figure 3 is a schematic diagram of a business process management system according to another embodiment of the present invention;

[0011] Figure 4 is a schematic diagram of a frequent path graph according to an embodiment of the present invention.

[0012] Description of Reference Numerals

[0013] 100: Business process management system;

[0014] 110: processor;

[0015] 120: storage device;

[0016] 121: Data mining module;

[0017] 1211: data preprocessing unit;

[0018] 1212: Frequent pattern mining unit;

[0019] 122: Path process matching module;

[0020] 1221: path flow matching unit;

[0021] 1222: support normalization unit;

[0022] 123: Process modeling and optimization module;

[0023] 1231: Process path modeling unit;

[0024] 1232: Visual presentation unit;

[0025] 301: Enterprise system operation log;

[0026] 302: Original business process;

[0027] 303: Frequent path graph;

[0028] 50S: event starting point;

[0029] 50E: Event end point;

[0030] 501A: Frequent path;

[0031] 501B: New business processes;

[0032] 510A: Warning Icon

[0033] 510B, 510C: process prompt icons;

[0034] 502, 503, 504, 505, 506, 507, 508, 509: events;

[0035] S210~S240: steps. DETAILED DESCRIPTION

[0036] Reference will now be made in detail to exemplary embodiments of the present invention, examples of which are illustrated in the accompanying drawings. Whenever possible, the same reference numerals are used in the drawings and the description to refer to the same or like parts.

[0037] Figure 1 FIG. 1 is a schematic diagram of a business process management system according to an embodiment of the present invention. Figure 1 , the business process management system 100 includes a processor 110 and a storage device 120. The processor 110 is coupled to the storage device 120. The storage device 120 stores a data mining module 121, a path process matching module 122, and a process modeling optimization module 123. In this embodiment, the business process management system 100 can be, for example, a computer host set up in an enterprise, or a host that communicates with the enterprise's database via a wired or wireless method or via a network connection to record and obtain the enterprise system operation log. In this embodiment, the business process management 100 can also be implemented by connecting a host computer or a server host to (or communicating with) multiple computer hardware devices. The multiple computer hardware devices can include, for example, a personal computer (PC), a workstation computer (Workstation computer), a mobile computer (Mobile computer), and a server computer (Server computer).

[0038] In this embodiment, the enterprise system operation log includes user behavior log, transaction data, data footprint, system configuration data, system operation data, system internal data change history data, micro-event gateway log, event occurrence timestamp, event associated person client code (Identify, ID), event name, event duration, request time, requester address, service name, service instance address assigned by the load balancer, status code, response time and Hyper Text Transfer Protocol (HTTP) proxy.

[0039] In the present embodiment, the processor 110 may include, for example, a central processing unit (CPU), or other programmable general-purpose or special-purpose microprocessor, digital signal processor (DSP), application specific integrated circuits (ASIC), programmable logic device (PLD), other similar processing circuits or a combination of these devices. The storage device 120 may include a memory and / or a database, wherein the memory may be, for example, a non-volatile memory (NVM). The storage device 120 may store relevant programs, modules, systems or algorithms for implementing various embodiments of the present invention, so that the processor 110 can access and execute to implement the relevant functions and operations described in various embodiments of the present invention. In this embodiment, the data mining module 121, the path process matching module 122 and the process modeling optimization module 123 can be implemented in a programming language such as JSON (JavaScript Object Notation), Extensible Markup Language (XML) or YAML, but the present invention is not limited to this.

[0040] Figure 2 FIG. 1 is a flowchart of a business process management system method according to an embodiment of the present invention. Figure 1 as well as Figure 2, the business process management system 100 can perform the following steps S210 to S240 to automatically provide reference information for the business process and automatically summarize the new path of the enterprise business process. In step S210, the processor 110 obtains the enterprise system operation log. In this embodiment, data points are buried in the enterprise system to record the enterprise system operation log (i.e., enterprise system operation data). In this regard, the processor 110 communicates with the system database by wired or wireless means to obtain the enterprise system operation log. In step S220, the processor 110 executes the data mining module 121 according to the enterprise system operation log to obtain a frequent path set including multiple event frequent paths. In this embodiment, the data mining module 121 can perform data analysis and data mining of the enterprise system operation log to aggregate the associated event list according to the enterprise system operation log to form a transaction set to be mined including multiple event chains. In this embodiment, the data mining module 121 generates the transaction set to be mined based on the method of depth-first search tree structure. Then, the data mining module 121 mines a frequent path set including multiple event frequent paths according to the transaction set to be mined. In this embodiment, the data mining module 121 extracts frequent event paths from the transaction set based on a mining algorithm.

[0041] In step S230, the processor 110 can generate a matching path set matching the original business process according to the frequent path set and the multiple original business processes through the path process matching module 122. In this embodiment, the path process matching module 122 starts searching from the longest frequent path during the path process matching process. In this embodiment, the path process matching module 122 matches the event frequent paths associated with the original business process in the frequent path set to generate a matching path set including multiple matching paths.

[0042] In this embodiment, the multiple business processes in the original business process can represent business behaviors and user operation behaviors executed by multiple computer hardware devices. In a specific embodiment, the original business process includes the main control computer, server host and user behavior log in the enterprise system operation log, transaction data, data footprint, system configuration data, system operation data, system internal data change history data, micro event gateway log, event occurrence timestamp, event associated person client code (Identify, ID), event name, event duration, request time, requester address, service name, service instance address assigned by the load balancer, status code, response time and Hyper Text Transfer Protocol (HTTP) proxy and other operations and data.

[0043] In step S240, the processor 110 can generate a frequent path graph according to the frequent path set through the process modeling optimization module 123. In this embodiment, the process modeling optimization module 123 uses each path sequence element (e.g., each individual event) in the frequent path set as a node of the graph to model the frequent path graph and generate the frequent path graph. In this embodiment, the process modeling optimization module 123 marks the node information (i.e., node data) of each graph node (i.e., path node) on the frequent path graph, such as the time consumption of each node of the path, the path support, etc.

[0044] In this way, the business process management system and method of the present invention can automatically mine and match multiple frequent event paths associated with the original business process based on the enterprise system operation log, and can establish a labeled frequent path graph based on the event nodes to automatically generate multiple call paths for establishing multiple application interface objects and application interfaces, and can automatically execute multiple application interface objects and application interfaces in sequence according to the call path to automatically generate new business paths, and visualize the frequent path set to generate a frequent path graph.

[0045] Figure 3 It is a schematic diagram of a business process management system according to another embodiment of the present invention. Figure 4 FIG. 1 is a schematic diagram of a frequent path diagram of an embodiment of the present invention. Figure 1 as well as Figure 3 , the data mining module 121 includes a data preprocessing unit 1211 and a frequent pattern mining unit 1212. The path process matching module 122 includes a path process matching unit 1221 and a support normalization unit 1222. The process modeling optimization module 123 includes a process path modeling unit 1231 and a visualization presentation unit 1232. In this embodiment, the data preprocessing unit 1211 performs data cleaning and event chain generation according to the enterprise system operation log to generate a transaction set including multiple event chains. And the data preprocessing unit 1211 provides the transaction set to the frequent pattern mining unit 1212. In this embodiment, during the data cleaning process of the data preprocessing unit 1211, the error event records and useless system information in the enterprise system operation log are eliminated, and then the required field information is filtered out to form a structured data set. For example, the required field information may be a successful request record with a response status code of 200 or 2xx in the gateway log, and the process of removing error event records may be removing error event records with a status code of 4xx (eg, 400, 404), but the present invention is not limited thereto.

[0046] In this embodiment, the data preprocessing unit 1211 regards event chains with the same event starting point in the enterprise system operation logs as the same event chain. Specifically, the data preprocessing unit 1211 identifies the request chain in the enterprise system operation logs to form the starting point of the event occurrence chain. In this embodiment, the event chain and the starting node include user occurrence events from outside the system, system automatically initiated events, and subsequent events of process flow. Then, the data preprocessing unit 1211 aggregates event chains with the same event starting point to generate a transaction set. In this embodiment, the data preprocessing unit 1211 can adopt a method based on the depth-first search tree structure to establish the transaction set.

[0047] Next, the frequent pattern mining unit 1212 performs frequent pattern mining based on the transaction set to generate a frequent path set. In this embodiment, the data mining module 121 executes different frequent pattern mining algorithms according to different mining scenarios to generate a frequent path set. For example, algorithms for candidate set splicing, tree-based algorithms, and recursive suffix algorithms. In this embodiment, during the process of the frequent pattern mining unit 1212 performing frequent pattern mining, the position of each event in the event chain (i.e., the occurrence path) cannot be changed or swapped. Specifically, the frequent pattern mining unit 1212 adopts sequence pattern mining. In addition, the frequent paths generated by the frequent pattern mining unit 1212 contain the most events. For example, a frequent path does not exist in the enterprise system operation logs as long as the frequent count (i.e., the number of times an event occurs) reaches the threshold, then it belongs to the frequent path. Specifically, the frequent pattern mining unit 1212 adopts the maximum frequent pattern mining (i.e., the path covering the most events).

[0048] For example, the processor 120 can execute the frequent pattern mining unit 1212 through the following definition to generate a frequent path set including multiple event frequent paths according to the design of, for example, the Apriori algorithm framework: S = {S1, S2, S3, …, S z} is the event set. The sequence T i = <S1, S2, S3, …, S k > (0 < k ≤ z) is an event chain path. k is the length of the occurrence path. O = {T1, T2, T3, …, T n} is the set of event paths to be mined. T is the set composed of sub-paths of all T i . For t ∈ T, c(t) represents the occurrence frequency of t in O, that is, the support degree of t. m is the frequent threshold (i.e., the minimum support degree). S1, S2, S3, …, S Z can represent each event.

[0049] In this embodiment, the path flow matching unit 1221 performs flow matching and flow expansion according to the frequent path set and the original business process to generate a matching path set. In this embodiment, in the path flow matching process, each frequent path is matched with the original business process starting from the longest (i.e., including the most events) frequent path. Specifically, when the original business process accurately matches a frequent path in the frequent path set, the path flow matching unit 1221 associates the frequent path with the original business process.

[0050] In another case, the path flow matching unit 1221 associates the frequent path with the largest support or the longest length among the frequent paths that partially match each other in the original business process set to the relevant original business process for process matching, so as to generate a matching path set including the frequent paths with the largest support and / or the longest length. Specifically, when the original business process is a sub-path of one or more frequent paths (i.e., the events of the original business process are the same as the events of part of the frequent paths), the path flow matching unit 1221 associates the frequent path with the largest support (i.e., the highest occurrence frequency) among all the matched frequent paths to the original business process. When one or more frequent paths are sub-paths of the original business process, the path flow matching unit 1221 associates the largest frequent path among the frequent paths that match this original business process to the original business process.

[0051] In another case, the path process matching unit 1221 uses the frequent paths in the frequent path set that are not matched with the original business process set as augmented business paths for process augmentation to generate a matching path set including augmented business paths. Specifically, when any frequent path in the frequent path set is not matched with the original business process, it means that this frequent path belongs to a new business path, and the path process matching unit 1221 adds this business path to the original business process to augment the business process. In another case, the path process matching unit 1221 determines the original business process that is not matched with the frequent path as infrequent (i.e., the number of occurrences is less than the support threshold) and is not associated with any frequent path.

[0052] Next, the path flow matching unit 1221 provides the matching path set to the support normalization unit 1222, and the support normalization unit 1222 performs support normalization according to the matching path set and the support of each path in the matching path set to generate a normalized support. In this embodiment, the support normalization unit 1222 converts the support between each two events into a value in the range of 0 to 1. The support normalization unit can use the equation Cu = (k-1 + c / n) / kmax to convert the support to [(k-1) / k max ,k / k max) interval. c is the frequency of p, and n is the size of the transaction set (i.e., the number of events). u is the normalized support. k is the length of the occurrence path.

[0053] In this embodiment, the process path modeling unit 1231 generates a frequent path graph according to the normalized support and the matching path set, and the visualization unit 1232 generates a labeled frequent path graph according to the frequent path graph and the node data in the frequent path graph (e.g., support, event occurrence time, event duration). In this embodiment, the process path modeling unit 1231 generates a frequent path graph (e.g., a map of the number of nodes in the matching path set) according to each matching path in the matching path set. Figure 4 ), and the frequent path graph includes a frequent path 501A that matches the original business process set. The frequent path 501A includes multiple events 502, 503, 504, 505, 506, 509, an event start point 50S and an event end point 50E. In addition, the frequent path graph also includes a new business process 501B in the frequent path set, and the new business process 501B includes multiple events 507, 508 and process prompt icons 510B, 510C.

[0054] In the present embodiment, the visualization unit 1232 marks the data or information of each node (i.e., each event) in the path diagram in the frequent path diagram. In the present embodiment, the visualization unit marks the average duration of the events for multiple nodes (i.e., events) of the frequent path diagram according to the event duration in the enterprise system operation log to generate a marked frequent path diagram. Specifically, the visualization unit 1232 marks the average duration of each event in the frequent path diagram. In addition, when the average duration of an event is greater than a time threshold (e.g., 2 minutes, 5 minutes) or the average time of the remaining events, the visualization unit 1232 marks the event 506 with a longer duration with a warning icon 510A in the frequent path diagram to provide a reference for the user to improve the process.

[0055] In this embodiment, the visualization unit 1232 generates a plurality of event support icons 502A, 503A, 504A, 505A, 506A, 507A, and 508A for the adjacent event support, and marks them in the frequent path graph. Specifically, in the frequent path graph, when the number of nodes under a node is 1, the support icon of this node is set to 1 (e.g. Figure 4 On the other hand, when the number of nodes under a node is greater than 1, the support icon of the node is set according to the support of the nodes under it (such as Figure 4504A, 504B and 504C), where the support value is greater than 0 and less than 1. In this way, the user can quickly and clearly know the status and information of the business process based on the markings of the frequent path map and the visual matching path, so as to improve the efficiency of users or enterprise managers in reviewing and improving business processes.

[0056] In summary, the business process management method and method of the present invention can automatically mine the largest and / or most frequent process paths based on the enterprise system operation log and the original business process, and establish a frequent path map based on the matching path matching the original business process, the support of each event, and the event duration, so as to provide operators or managers with reference information and suggestions for optimizing enterprise processes, and provide process review and improvement efficiency based on visualized information.

[0057] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A business process management system, characterized in that: include: A storage device for storing a plurality of modules; as well as A processor, coupled to the storage device, executes the multiple modules, The processor obtains the enterprise system operation log, and executes a data mining module according to the enterprise system operation log to obtain a frequent path set including a plurality of event frequent paths. The processor inputs the frequent path set and a plurality of original business processes into a path process matching module, and executes the path process matching module to generate a matching path set matching the original business process. The processor executes a process modeling optimization module according to the matching path set to generate a frequent path graph; The path process matching module includes a path process matching unit and a support normalization unit. The path process matching unit performs process matching and process expansion according to the frequent path set and the original business process to generate the matching path set, and provides the matching path set to the support normalization unit. The support normalization unit performs support normalization according to the matching path set and the support of each path in the matching path set to generate the normalized support.

2. The business process management system according to claim 1, characterized in that: The data mining module includes a data preprocessing unit and a frequent pattern mining unit. The data preprocessing unit performs data cleaning and event chain generation according to the enterprise system operation log to generate a transaction set including multiple event chains, and provides the transaction set to the frequent pattern mining unit. The frequent pattern mining unit performs frequent pattern mining according to the transaction set to generate the frequent path set.

3. The business process management system according to claim 2, characterized in that: The frequent pattern mining unit performs frequent pattern mining based on a candidate set concatenation algorithm, a tree algorithm or a recursive suffix algorithm to generate the frequent path set.

4. The business process management system according to claim 2, characterized in that: The data preprocessing unit regards the event chains with the same event starting point in the enterprise system operation log as the same event chain to generate the transaction set including the event chain.

5. The business process management system according to claim 2, characterized in that: The event chain includes events generated by users, events automatically initiated by the system, and subsequent events of process flow.

6. The business process management system according to claim 1, characterized in that: The path process matching module uses the frequent paths in the frequent path set that are not matched with the original business process set as augmented business paths to perform process augmentation, so as to generate the matching path set including the augmented business paths.

7. The business process management system according to claim 1, characterized in that: The path process matching unit associates the frequent path with the largest support or the longest length among the frequent paths in the frequent path set that partially match each other in the original business process set to the relevant original business process for process matching, so as to generate the matching path set including the frequent path with the largest support and / or the longest length.

8. The business process management system according to claim 1, characterized in that: The process modeling optimization module includes a process path modeling unit and a visualization presentation unit. The process path modeling unit generates a frequent path graph according to the normalized support and the matching path set. The visual presentation unit generates the labeled frequent path graph according to the frequent path graph and the node data in the frequent path graph.

9. The business process management system according to claim 8, characterized in that: The visual presentation unit marks the average duration of events on multiple nodes of the frequent path diagram according to the event duration in the enterprise system operation log, so as to generate the marked frequent path diagram.

10. A business process management method, characterized in that: include: Obtain enterprise system operation logs; Executing a data mining module according to the enterprise system operation log to obtain a frequent path set including a plurality of event frequent paths; Generate a matching path set matching the original business process according to the frequent path set and a plurality of original business processes through a path process matching module; as well as Generate a frequent path graph according to the matching path set through a process modeling optimization module; The step of generating the matching path set matching the original business process includes: The path process matching unit is used to perform process matching and process expansion to generate the matching path set; The support normalization unit is used to perform support normalization to generate the normalized support.

11. The business process management method according to claim 10, characterized in that: The step of obtaining the frequent path set including the frequent path of the event comprises: The data preprocessing unit is used to perform data cleaning and event chain generation to generate a transaction set including multiple event chains; The frequent pattern mining unit is used to perform frequent pattern mining to generate the frequent path set.

12. The business process management method according to claim 11, characterized in that: The frequent pattern mining unit performs frequent pattern mining based on a candidate set concatenation algorithm, a tree algorithm or a recursive suffix algorithm to generate the frequent path set.

13. The business process management method according to claim 11, characterized in that: The step of generating the transaction set including the event chain comprises: The data preprocessing unit treats the event chains in the enterprise system operation log that have the same event starting point as the same event chain to generate the transaction set including the event chain.

14. The business process management method according to claim 11, characterized in that: The event chain includes events generated by users, events automatically initiated by the system, and subsequent events of process flow.

15. The business process management method according to claim 10, characterized in that: The step of generating the matching path set comprises: The path process matching unit uses the frequent paths in the frequent path set that are not matched with the original business process set as augmented business paths to perform process augmentation, so as to generate the matching path set including the augmented business paths.

16. The business process management method according to claim 10, characterized in that: The step of generating the matching path set comprises: The path process matching unit associates the frequent path with the largest support or the longest length among the frequent paths in the frequent path set that partially match each other in the original business process set to the relevant original business process for process matching, so as to generate the matching path set including the frequent path with the largest support and / or the longest length.

17. The business process management method according to claim 10, characterized in that: The steps of generating the frequent path graph include: Generate a frequent path graph according to the normalized support and the matching path set by a process path modeling unit; The frequent path graph with labels is generated by a visual presentation unit according to the frequent path graph and the node data in the frequent path graph.

18. The business process management method according to claim 17, characterized in that: The steps of generating the labeled frequent path graph include: The visual presentation unit marks the average duration of events on multiple nodes of the frequent path graph to generate the marked frequent path graph.

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