Title:
Process Mining, Discovery, and Integration Using Distance Measures

dc.contributor.author Bae, Joonsoo
dc.contributor.author Caverlee, James
dc.contributor.author Liu, Ling
dc.contributor.author Rouse, William B.
dc.contributor.corporatename Georgia Institute of Technology. College of Computing
dc.contributor.corporatename Chonbuk National University, South Korea
dc.date.accessioned 2007-05-10T18:25:58Z
dc.date.available 2007-05-10T18:25:58Z
dc.date.issued 2006
dc.description.abstract Business processes continue to play an important role in today's service-oriented enterprise computing systems. Mining, discovering, and integrating process-oriented services has attracted growing attention in the recent year. In this paper we present a quantitative approach to modeling and capturing the similarity and dissimilarity between different workflow designs. Concretely, we introduce a graph-based distance measure and a framework for utilizing this distance measure to mine the process repository and discover workflow designs that are similar to a given design pattern or to produce one integrated workflow design by merging two or more business workflows of similar designs. We derive the similarity measures by analyzing the workflow dependency graphs of the participating workflow processes. Such an analysis is conducted in two phases. We first convert each workflow dependency graph into a normalized process network matrix. Then we calculate the metric space distance between the normalized matrices. This distance measure can be used as a quantitative and qualitative tool in process mining, process merging, and process clustering, and ultimately it can reduce or minimize the costs involved in design, analysis, and evolution of workflow systems. en
dc.identifier.uri http://hdl.handle.net/1853/14340
dc.language.iso en_US en
dc.publisher Georgia Institute of Technology en
dc.relation.ispartofseries SCS Technical Report ; GIT-CSS-06-06 en
dc.subject Business process management systems en
dc.subject Process mining, discovery, and integration en
dc.subject Web services en
dc.title Process Mining, Discovery, and Integration Using Distance Measures en
dc.type Text
dc.type.genre Technical Report
dspace.entity.type Publication
local.contributor.author Liu, Ling
local.contributor.author Rouse, William B.
local.contributor.corporatename College of Computing
local.contributor.corporatename School of Computer Science
local.relation.ispartofseries College of Computing Technical Report Series
local.relation.ispartofseries School of Computer Science Technical Report Series
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relation.isSeriesOfPublication 26e8e5bc-dc81-469c-bd15-88e6f98f741d
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