A Focused Crawler by Segmentation of Context Information 


Vol. 12,  No. 6, pp. 697-702, Oct.  2005
10.3745/KIPSTB.2005.12.6.697


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  Abstract

The focused crawler is a topic-driven document-collecting crawler that was suggested as a promising alternative of maintaining up-to-date web document indices in search engines. A major problem inherent in previous focused crawlers is the liability of missing highly relevant documents that are linked from off-topic documents. This problem mainly originated from the lack of consideration of structural information in a document. Traditional weighting method such as TFIDF employed in document classification can lead to this problem. In order to improve the performance of focused crawlers, this paper proposes a scheme of locality-based document segmentation to determine the relevance of a document to a specific topic. We segment a document into a set of sub-documents using contextual features around the hyperlinks. This information is used to determine whether the crawler would fetch the documents that are linked from hyperlinks in an off-topic document.

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  Cite this article

[IEEE Style]

C. H. Cho, N. Y. Lee, J. B. Kang, J. Y. Yang, J. M. Choi, "A Focused Crawler by Segmentation of Context Information," The KIPS Transactions:PartB , vol. 12, no. 6, pp. 697-702, 2005. DOI: 10.3745/KIPSTB.2005.12.6.697.

[ACM Style]

Chang Hee Cho, Nam Yong Lee, Jin Bum Kang, Jae Young Yang, and Joong Min Choi. 2005. A Focused Crawler by Segmentation of Context Information. The KIPS Transactions:PartB , 12, 6, (2005), 697-702. DOI: 10.3745/KIPSTB.2005.12.6.697.