Workflow Mining: Discovering Process Models from Event Logs
IEEE Transactions on Knowledge and Data Engineering
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An Efficient Workcase Classification Method and Tool in Workflow Mining
Proceedings of the Fourth Annual ACIS International Conference on Computer and Information Science
Mining Workflow Patterns through Event-Data Analysis
SAINT-W '05 Proceedings of the 2005 Symposium on Applications and the Internet Workshops
Active User-Based and Ontology-Based Web Log Data Preprocessing for Web Usage Mining
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Characterizing Workflow Nets Using Regions
SYNASC '06 Proceedings of the Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
A workflow mining method through model rewriting
CRIWG'05 Proceedings of the 11th international conference on Groupware: design, Implementation, and Use
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Collaboration environment supports organizations and individuals sharing resource, taking advantage of their knowledge, and cooperating to accelerate their work especially for large scale problem. To find out the law of collaboration works through an automated approach is beneficial to improve collaboration environment, and is known as behavior pattern discovering. Traditionally, preprocessing is considered as data preparation, and mainly covers four kinds of methods as variable selection, sample selection, variable construction, and variable transformation. The preprocessing in behavior pattern discovering focuses on sample selection and variable transformation, because of the four challenges in behavior pattern discovering that the lack of reference knowledge, the cutting short of continuous recorded data, the transformation of resource data according to meanings, and the utilization of various recorded information. This paper emphasizes the indicators that information reservation and data reduction, and points out the major challenge in preprocessing is how to balance the two. Further more, the paper gives out effective algorithms on variable transformation and event sequence dividing. Such algorithms assure that the whole behavior pattern discovering approach works under an efficient and automatic way.