Knowledge maps for composite e-services: A mining-based system platform coupling with recommendations

Duen-Ren Liu*, Chih Kun Ke, Jia Yuan Lee, Chun Feng Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


Providing various e-services on the Internet by enterprises is an important trend in e-business. Composite e-services, which consist of various e-services provided by different e-service providers, are complex processes that require the cooperation among cross-organizational e-service providers. The flexibility and success of e-business depend on effective knowledge support to access related information resources of composite e-services. Thus, providing effective knowledge support for accessing composite e-services is a challenging task. This work proposes a knowledge map platform to provide an effective knowledge support for utilizing composite e-services. A data mining approach is applied to extract knowledge patterns from the usage records of composite e-services. Based on the mining result, topic maps are employed to construct the knowledge map. Meanwhile, the proposed knowledge map is integrated with recommendation capability to generate recommendations for composite e-services via data mining and collaborative filtering techniques. A prototype system is implemented to demonstrate the proposed platform. The proposed knowledge map enhanced with recommendation capability can provide users customized decision support to effectively utilize composite e-services.

Original languageEnglish
Pages (from-to)700-716
Number of pages17
JournalExpert Systems with Applications
Issue number1
StatePublished - 1 Jan 2008


  • Composite e-service
  • Data mining
  • Knowledge maps
  • Recommendation
  • Topic maps


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