Knowledge discovery in services (KDS): Aggregating software services to discover enterprise mashups

M. Brian Blake, Michael E. Nowlan

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

Service mashup is the act of integrating the resulting data of two complementary software services into a common picture. Such an approach is promising with respect to the discovery of new types of knowledge. However, before service mashup routines can be executed, it is necessary to predict which services (of an open repository) are viable candidates. Similar to Knowledge Discovery in Databases (KDD), we introduce the Knowledge Discovery in Services (KDS) process that identifies mashup candidates. In this work, the KDS process is specialized to address a repository of open services that do not contain semantic annotations. In these situations, specialized techniques are required to determine equivalences among open services with reasonable precision. This paper introduces a bottom-up process for KDS that adapts to the environment of services for which it operates. Detailed experiments are discussed that evaluate KDS techniques on an open repository of services from the Internet and on a repository of services created in a controlled environment.

Original languageEnglish (US)
Article number5582089
Pages (from-to)889-901
Number of pages13
JournalIEEE Transactions on Knowledge and Data Engineering
Volume23
Issue number6
DOIs
StatePublished - May 5 2011

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Keywords

  • Interactive exploration and discovery
  • knowledge management applications
  • service mashup
  • web-based services.

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Information Systems
  • Computer Science Applications

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