Combining text and link analysis for focused crawling

  • Authors:
  • George Almpanidis;Constantine Kotropoulos

  • Affiliations:
  • Department of Infomatics, Aristotle University of Thessaloniki, Thessaloniki, Greece;Department of Infomatics, Aristotle University of Thessaloniki, Thessaloniki, Greece

  • Venue:
  • ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
  • Year:
  • 2005

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Abstract

The number of vertical search engines and portals has rapidly increased over the last years, making the importance of a topic-driven (focused) crawler evident. In this paper, we develop a latent semantic indexing classifier that combines link analysis with text content in order to retrieve and index domain specific web documents. We compare its efficiency with other well-known web information retrieval techniques. Our implementation presents a different approach to focused crawling and aims to overcome the limitations of the necessity to provide initial training data while maintaining a high recall/precision ratio.