• Title/Summary/Keyword: workflow process analytics

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Workflow Process-Aware Data Cubes and Analysis (워크플로우 프로세스 기반 데이터 큐브 및 분석)

  • Jin, Min-hyuck;Kim, Kwang-hoon Pio
    • Journal of Internet Computing and Services
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    • v.19 no.6
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    • pp.83-89
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    • 2018
  • In workflow process intelligence and systems, workflow process mining and analysis issues are becoming increasingly important. In order to improve the quality of workflow process intelligence, it is essential for an efficient and effective data center storing workflow enactment event logs to be provisioned in carrying out the workflow process mining and analytics. In this paper, we propose a three-dimensional process-aware datacube for organizing workflow enterprise data centers to efficiently as well as effectively store the workflow process enactment event logs in the XES format. As a validation step, we carry out an experimental process mining to show how much perfectly the process-aware datacubes are suitable for discovering workflow process patterns and its analytical knowledge, like enacted proportions and enacted work transferences, from the workflow process enactment event histories. Finally, we confirmed that it is feasible to discover the fundamental control-flow patterns of workflow processes through the implemented workflow process mining system based on the process-aware data cube.

Disjunctive Process Patterns Refinement and Probability Extraction from Workflow Logs

  • Kim, Kyoungsook;Ham, Seonghun;Ahn, Hyun;Kim, Kwanghoon Pio
    • Journal of Internet Computing and Services
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    • v.20 no.3
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    • pp.85-92
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    • 2019
  • In this paper, we extract the quantitative relation data of activities from the workflow event log file recorded in the XES standard format and connect them to rediscover the workflow process model. Extract the workflow process patterns and proportions with the rediscovered model. There are four types of control-flow elements that should be used to extract workflow process patterns and portions with log files: linear (sequential) routing, disjunctive (selective) routing, conjunctive (parallel) routing, and iterative routing patterns. In this paper, we focus on four of the factors, disjunctive routing, and conjunctive path. A framework implemented by the authors' research group extracts and arranges the activity data from the log and converts the iteration of duplicate relationships into a quantitative value. Also, for accurate analysis, a parallel process is recorded in the log file based on execution time, and algorithms for finding and eliminating information distortion are designed and implemented. With these refined data, we rediscover the workflow process model following the relationship between the activities. This series of experiments are conducted using the Large Bank Transaction Process Model provided by 4TU and visualizes the experiment process and results.

BPAF2.0: Extended Business Process Analytics Format for Mining Process-driven Social Networks (BPAF2.0: 프로세스기반 소셜 네트워크 마이닝을 위한 비즈니스 프로세스 분석로그 포맷의 확장 표준)

  • Jeon, Myung-Hoon;Ahn, Hyun;Kim, Kwang-Hoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.12B
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    • pp.1509-1521
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    • 2011
  • WfMC, which is one of the international standardization organizations leading the business process and workflow technologies, has been officially released the BPAF1.0 that is a standard format to record process instances' event logs according as the business process intelligence mining technologies have recently issued in the business process and workflow literature. The business process mining technologies consist of two groups of algorithms and their analysis techniques; one is to rediscover flow-oriented process-intelligence, such as control-flow, data-flow, role-flow, and actor-flow intelligence, from process instances' event logs, and the other has something to do with rediscovering relation-oriented process-intelligence like process-driven social networks and process-driven affiliation networks from the event logs. The current standardized format of BPAF1.0 aims at only supporting the control-flow oriented process-intelligence mining techniques, and so it is unable to properly support the relation-oriented process-intelligence mining techniques. Therefore, this paper tries to extend the BPAF1.0 so as to reasonably support the relation-oriented process-intelligence mining techniques, and the extended BPAF is termed BPAF2.0. Particularly, we have a plan to standardize the extended BPAF2.0 as not only the national standard specifications through the e-Business project group of TTA, but also the international standard specifications of WfMC.