Abstract
Focused crawlers are programs designed to selectively retrieve Web pages relevant to a specific domain for the use of domain-specific search engines. Tunneling is a heuristic-based method that solves global optimization problem. In this paper we use content block algorithm to enhance focused crawler’s ability of traversing tunnel. The novel Algorithm not only avoid granularity too coarse when evaluation on the whole page but also avoid granularity too fine based on link-context. A comprehensive experiment has been conducted, the result shows obviously that this approach outperforms BestFirst and Anchor text algorithm both in harvest ratio and efficiency.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
De Bra, P., et al.: Information Retrieval in Distributed Hypertexts. In: Proc. 4th Int’l Conf. Intelligent Multimedia Information Retrieval Systems and Management(RIAO 1994), Center of High Int’l Studies of Documentary Information Retrieval(CID), pp. 481–491 (1994)
Hersovici, M., et al.: The SharkSearch Algorithm-An Application: Tailored Web Site Mapping Computer. Networks and ISDN Systems 30(1-7), 317–326
McCallum, A., et al.: Building Domain-Specific Search Engines with Machine Learning Techniques. In: AAAI Spring Symp. Intelligent Agents in Cyberspace, pp. 28–39. AAAI Press, Menlo Park (1999)
Kao, H., Lin, S., Ho, J., Chen, M.-S.: Mining web informative structures and contents based on entropy analysis. IEEE Transactions on Knowledge and Data Engineering 16(1), 41–44 (2004)
Bergmark, D., Lagoze, C., Sbityakov, A.: Focused Crawls, Tunneling, and Digital Libraries. In: Proc. Proc. Of the 6th European Conference on Digital Libaries, Rome, Italy (2002b)
Ziv, B.Y., et al.: Template Detcetion via Data Mining and its Applications. In: Proc. 11th International World Wide Web Conference (2002)
Chakrabarti, S.: Integrating the document object model with hyperlinks for enhanced topic distillation and information extraction. In: Proc. 10th International World Wide Web Conference (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Luo, N., Zuo, W., Yuan, F., Zhang, C. (2006). A New Method for Focused Crawler Cross Tunnel. In: Wang, GY., Peters, J.F., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2006. Lecture Notes in Computer Science(), vol 4062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11795131_92
Download citation
DOI: https://doi.org/10.1007/11795131_92
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36297-5
Online ISBN: 978-3-540-36299-9
eBook Packages: Computer ScienceComputer Science (R0)