An inner-enterprise knowledge recommender system

Lu Zhen, George Q. Huang, Zuhua Jiang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

39 Citations (Scopus)


This paper proposes a model of the inner-enterprise knowledge recommender system. Among an organization, different members have different demands for knowledge in different context. Comparing with traditional knowledge query way, the knowledge recommender systems supply us a more proactive way that could deliver the proper knowledge to the proper people at the proper time. The recommendation mechanism is based on semantic matching on context information from both users' side and knowledge's side. Recommendation rules are also maintained in the recommendation engine, which is the core module in the system. By adjusting the rules, the configuration of the knowledge recommender system could be adapted to different users. This paper presents the system design as well as some key technologies analysis, and also discusses the advantages and preconditions for implementing the proposed system.

Original languageEnglish
Pages (from-to)1703-1712
Number of pages10
JournalExpert Systems with Applications
Issue number2
Publication statusPublished - Mar 2010
Externally publishedYes


  • Context awareness
  • Knowledge management
  • Recommender system

ASJC Scopus subject areas

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence


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