Improved algorithms for topic distillation in a hyperlinked environment
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Automatic resource compilation by analyzing hyperlink structure and associated text
WWW7 Proceedings of the seventh international conference on World Wide Web 7
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
The stochastic approach for link-structure analysis (SALSA) and the TKC effect
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Proceedings of the 10th international conference on World Wide Web
Link analysis, eigenvectors and stability
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Site abstraction for rare category classification in large-scale web directory
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
A study of relevance propagation for web search
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Topic distillation via sub-site retrieval
Information Processing and Management: an International Journal - Special issue: AIRS2005: Information retrieval research in Asia
Level-Biased statistics in the hierarchical structure of the web
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Subsite retrieval: a novel concept for topic distillation
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
Calculating webpage importance with site structure constraints
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
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In order to get high-quality web pages, search engines often resort retrieval pages by their ranks. The rank is a kind of measurement of importance of pages. Famous ranking algorithms, including PageRank and HITS, make use of hyperlinks to compute the importance. Those algorithms consider all hyperlinks identically in sense of recommendation. However, we find that the World Wide Web is actually organized with the natural multi-level structure. Benefiting from the level properties of pages, we can describe the recommendation of hyperlinks more reasonably and precisely. With this motivation, a new level-based link analysis algorithm is proposed in this paper. In the proposed algorithm, the recommendation weight of each hyperlink is computed with the level properties of its two endings. Experiments on the topic distillation task of TREC2003 web track show that our algorithm can evidently improve searching results as compared to previous link analysis methods.