ExNa: An efficient search pattern for semantic search engines

Xiao Wei, Dajun Zeng

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

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)
JournalConcurrency Computation Practice and Experience
DOIs
StateAccepted/In press - 2016
Externally publishedYes

Keywords

  • Big data
  • Index structure
  • Interaction process
  • Search pattern
  • Semantic search
  • User profile

ASJC Scopus subject areas

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

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