2011 AMultilevelUNLConceptbasedSearc

• (Umamaheswari et al., 2011) ⇒ E. Umamaheswari, T. V. Geetha, Ranjani Parthasarathi, and Madhan Karky. (2011). “A Multilevel UNL Concept based Searching and Ranking.” In: Proceedings of WEBIST 2011.

Subject Headings: Ontology Search System

Cited By

• http://scholar.google.com/scholar?q=%222011%22+A+Multilevel+UNL+Concept+based+Searching+and+Ranking.

Quotes

Author Keywords

• CoReS; UNL; Concept relation search and ranking; Query Expansion; Query Translation.

Abstract

The recent advances in search engines have resulted in a huge explosion of available web documents. Understanding the content on the web and providing meaningful search results to the user have become essential for any search engine. This paper proposes CoReS, a multilevel Concept based Searching and Ranking Algorithm which retrieves and ranks the documents based on the concepts and relationships between the concepts. The search and rank methodology is based on Universal Networking Language (UNL) representation of the documents. The UNL Index based query expansion technique is used to provide more meaningful results to the user. The algorithm has been evaluated on a corpus of tourism documents, and its performance compared with keyword based search. The mean average precision of the concept based search is found to be 0.75 while the keyword based search has a MAP score of 0.45.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2011 AMultilevelUNLConceptbasedSearc	E. Umamaheswari T. V. Geetha Ranjani Parthasarathi Madhan Karky			A Multilevel UNL Concept based Searching and Ranking.