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Mining social networks: Uncovering interaction patterns in business processes

Author(s)
van der Aalst, W.M.P.Song, Minseok
Issued Date
2004
DOI
10.1007/978-3-540-25970-1_16
URI
https://scholarworks.unist.ac.kr/handle/201301/4587
Fulltext
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=35048882847
Citation
BUSINESS PROCESS MANAGEMENT, v.3080, pp.244 - 260
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.
Publisher
SPRINGER-VERLAG BERLIN
ISSN
0302-9743

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