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Ranking Tagged Resources Using Social Semantic Relevance

Author

Listed:
  • Anjali Thukral

    (University of Delhi, India)

  • Hema Banati

    (Dyal Singh College, India)

  • Punam Bedi

    (University of Delhi, India)

Abstract

The WWW today is overwhelmed with information on almost every topic. Therefore, relevance ranking of web pages to a user’s expectations is a challenge, rather than retrieving a collection of thousands of web pages selected by keyword matching. This paper presents an approach to rank tagged web pages retrieved from a Social Bookmarking Site for a learner who needs web resources containing content on a given topic. Besides the popularity of the web page in the community, the relevance of a web page for ranking is computed based on the semantic distance between tags and a given topic using domain ontology. An experimental study has been conducted to evaluate the ranks generated by the proposed approach. The test collection was created using a questionnaire which was designed to judge the crawled web pages for their graded relevance on a topic.

Suggested Citation

  • Anjali Thukral & Hema Banati & Punam Bedi, 2011. "Ranking Tagged Resources Using Social Semantic Relevance," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 1(3), pages 15-34, July.
    • Handle: RePEc:igg:jirr00:v:1:y:2011:i:3:p:15-34
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