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dc.citation.endPage 260 -
dc.citation.startPage 244 -
dc.citation.title BUSINESS PROCESS MANAGEMENT -
dc.citation.volume 3080 -
dc.contributor.author van der Aalst, W.M.P. -
dc.contributor.author Song, Minseok -
dc.date.accessioned 2023-12-22T11:07:54Z -
dc.date.available 2023-12-22T11:07:54Z -
dc.date.created 2014-05-14 -
dc.date.issued 2004 -
dc.description.abstract Increasingly information systems log historic information in a systematic way. Workflow management systems, but also ERP, CRM, SCM, and B2B systems often provide a so-called "event log", i.e., a log recording the execution of activities. Unfortunately, the information in these event logs is rarely used to analyze the underlying processes. Process mining aims at improving this by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs. This paper focuses on the mining social networks. This is possible because event logs typically record information about the users executing the activities recorded in the log. To do this we combine concepts from workflow management and social network analysis. This paper introduces the approach, defines metrics, and presents a tool to mine social networks from event logs. -
dc.identifier.bibliographicCitation BUSINESS PROCESS MANAGEMENT, v.3080, pp.244 - 260 -
dc.identifier.doi 10.1007/978-3-540-25970-1_16 -
dc.identifier.issn 0302-9743 -
dc.identifier.scopusid 2-s2.0-35048882847 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/4587 -
dc.identifier.url http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=35048882847 -
dc.identifier.wosid 000222566300016 -
dc.language 영어 -
dc.publisher SPRINGER-VERLAG BERLIN -
dc.title Mining social networks: Uncovering interaction patterns in business processes -
dc.type Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -

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