IJMLC 2013 Vol.3(4): 357-360 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.337

An Application of Topic Map-Based Ontology Generated from Wikipedia for Query Expansion

S. Eslami and E. Nazemi

Abstract—Topic maps are a Semantic Web technology for semantic annotation of resources to enhance the quality of search output. The main idea of this research is to present a query expansion method using topic maps-based ontology for query expansion process, furthermore this paper proposed a novel automatic approach to construct topic maps from Wikipedia XML corpus. Wikipedia is general purpose, freely available online, is containing up to date information so it is a suitable option for topic map development. The proposed model is implemented and then applied on a test collection. The results show that using topic map-based ontology in query expansion process improves search accuracy in keyword-based information retrieval.

Index Terms—Ontology, information retrieval, semantic web, topic maps, query expansion.

Saeedeh Eslami is now with the National Library and Archive of Iran Tehran, Iran (e-mail: s-eslami@nlai.ir, eslami.saeedeh@gmail.com, phone: +9881622440). Eslam Nazemi was with Shahid Beheshti University (SBU), Tehran, Iran. He is now with the Electrical and Computer Engineering Faculty (e-mail: nazemi@sbu.ac.ir).

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Cite:S. Eslami and E. Nazemi, "An Application of Topic Map-Based Ontology Generated from Wikipedia for Query Expansion," International Journal of Machine Learning and Computing vol.3, no. 4, pp. 357-360, 2013.

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Scopus (since 2017), Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net