Research Article Open Access

Context Disambiguation Based Semantic Web Search for Effective Information Retrieval

M. Barathi and S. Valli


Problem statement: Search queries are short and ambiguous and are insufficient for specifying precise user needs. To overcome this problem, some search engines suggest terms that are semantically related to the submitted queries, so that users can choose from the suggestions based on their information needs. Approach: In this study, we introduce an effective approach that captures the user’s specific context by using the WordNet based semantic relatedness measure and the measures of joint keyword occurrences in the web page. Results: The context of the user query is identified and formulated. The user query is enriched to get more relevant web pages that the user needs. Conclusion: Experimental results show that our approach has better precision and recall than the existing methods.

Journal of Computer Science
Volume 7 No. 4, 2011, 548-553


Submitted On: 21 February 2011 Published On: 4 April 2011

How to Cite: Barathi, M. & Valli, S. (2011). Context Disambiguation Based Semantic Web Search for Effective Information Retrieval. Journal of Computer Science, 7(4), 548-553.

  • 4 Citations



  • Context disambiguation
  • information retrieval
  • WordNet based semantic
  • similarity measures
  • K-core algorithm
  • semantic similarity
  • search engine