ExNa: an efficient search pattern for semantic search engines

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Recent years have witnessed the emergence of new types of semantic search engines which attempt to overcome the defects of the traditional search engines by providing different search patterns. A big question here is that in order to achieve the semantic search engines (SSEs), what type(s) of search patterns should SSEs support? To help seek one of the many possible answers, in this paper we start with classifying and comparing current search engines, particularly from the perspective of search patterns which consist of index structure, user profiles, and interaction mechanism. We then present a novel search pattern named ExNa by defining its model and basic operations in detail. To validate the ExNa search pattern, we develop a prototype search engine named KNOWLE, and the experimental results show that KNOWLE equipped with ExNa can improve both the efficiency of the entire system when compared with search engines of other search patterns.

Original languageEnglish (US)
Pages (from-to)4107-4124
Number of pages18
JournalConcurrency Computation Practice and Experience
Issue number15
StatePublished - Oct 1 2016
Externally publishedYes


  • big data
  • index structure
  • interaction process
  • search pattern
  • semantic search
  • user profile

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Computational Theory and Mathematics


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