Semantic Relatedness Measures for Identifying Relationships in Product Development Processes

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Witherell, Paul
Krishnamurty, Sundar
Grosse, Ian
Wileden, Jack
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Center for e-Design

The Center for e-Design is a cooperative research center combining industry needs with academic resources to produce more efficient, effective, and collaborative electronic design processes and tools. Many high-tech companies and agencies face engineering challenges that limit the evolution of systems and products. The Center is committed to resolving these challenges through creative and innovative research. Center activities focus on fundamental research, research test beds, engineering education, and technology transfer. The Center for e-Design is a National Science Foundation Industry/University Cooperative Research Center.

Current Participating Institutions: Brigham Young University, University of Illinois at Urbana-Champaign, Iowa State University (lead institution), Oregon State University, University at Buffalo–The State University of New York, University of Massachusetts Amherst, and Wayne State University.

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The Semantic Web, especially in relation to ontologies, provides a structured, formal framework for knowledge interoperability. This trait has been exploited by both the biomedical community in development of the Human Gene Ontology [1] and also by geographers in development of geospatial ontologies [2]. Using semantic relatedness techniques, researchers from both communities have been able to develop and integrate comprehensive knowledge bases. Beyond knowledge integration, semantic relatedness techniques have also been able to provide each community with a unique insight into relationships between concepts in their respective domains. In the engineering community, semantic relatedness techniques promise to provide similar insight into product development processes. This paper explores the application of semantic relatedness techniques to ontologies as a means towards improved knowledge management in product development processes. Several different semantic relatedness techniques are reviewed, including a recently developed meronomic technique specific to domain ontologies. Three of these techniques are adopted to create a semantic relatedness measure specifically designed to identify and rank underlying relationships that exist between aspects of the product development process. Four separate case studies are then presented to evaluate the relative accuracy of the developed algorithm and then determine its effectiveness in exposing underlying relationships.


This article is from Proceedings of the ASME 2009 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (2009): Paper No. DETC2009-87624, pp. 395-408, doi:10.1115/DETC2009-87624. Posted with permission.

Thu Jan 01 00:00:00 UTC 2009