Abstract
Traditional ranking models used in Web search engines rely on a static snapshot of the Web graph, basically the link structure of the Web documents. However, visitors’ browsing activities indicate the importance of a document. In the traditional static models, the information on document importance conveyed by interactive browsing is neglected. The nowadays Web server/surfer model lacks the ability to take advantage of user interaction for document ranking. We enhance the ordinary Web server/surfer model with a mechanism inspired by swarm intelligence to make it possible for the Web servers to interact with Web surfers and thus obtain a proper local ranking of Web documents. The proof-of-concept implementation of our idea demonstrates the potential of our model. The mechanism can be used directly in deployed Web servers which enable on-the-fly creation of rankings for Web documents local to a Web site. The local rankings can also be used1 as input for the generation of global Web rankings in a decentralized way.
Please refer to our companion paper [3] on our Ranking Algebra.
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© 2003 Springer-Verlag Berlin Heidelberg
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Wu, J., Aberer, K. (2003). Swarm Intelligent Surfing in the Web. In: Lovelle, J.M.C., RodrĂguez, B.M.G., Gayo, J.E.L., del Puerto Paule Ruiz, M., Aguilar, L.J. (eds) Web Engineering. ICWE 2003. Lecture Notes in Computer Science, vol 2722. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45068-8_80
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DOI: https://doi.org/10.1007/3-540-45068-8_80
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