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Song, Minseok
Business Process Intelligence(BPI) Lab
Research Interests
  • Process mining

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Discovering social networks from event logs

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Title
Discovering social networks from event logs
Author
Van Der Aalst, W.M.P.Reijers, H.A.Song, Minseok
Keywords
Business process management; Data mining; Petri nets; Process mining; Social network analysis; Workflow management
Issue Date
200512
Publisher
SPRINGER
Citation
COMPUTER SUPPORTED COOPERATIVE WORK-THE JOURNAL OF COLLABORATIVE COMPUTING, v.14, no.6, pp.549 - 593
Abstract
Process mining techniques allow for the discovery of knowledge based on so-called "event logs", i.e., a log recording the execution of activities in some business process. Many information systems provide such logs, e.g., most WFM, ERP, CRM, SCM, and B2B systems record transactions in a systematic way. Process mining techniques typically focus on performance and control-flow issues. However, event logs typically also log the performer, e.g., the person initiating or completing some activity. This paper focuses on mining social networks using this information. For example, it is possible to build a social network based on the hand-over of work from one performer to the next. By combining concepts from workflow management and social network analysis, it is possible to discover and analyze social networks. This paper defines metrics, presents a tool, and applies these to a real event log within the setting of a large Dutch organization.
URI
http://scholarworks.unist.ac.kr/handle/201301/4585
DOI
http://dx.doi.org/10.1007/s10606-005-9005-9
ISSN
0925-9724
Appears in Collections:
SBA_Journal Papers

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