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SIGIR
2004
ACM

Block-level link analysis

13 years 9 months ago
Block-level link analysis
Link Analysis has shown great potential in improving the performance of web search. PageRank and HITS are two of the most popular algorithms. Most of the existing link analysis algorithms treat a web page as a single node in the web graph. However, in most cases, a web page contains multiple semantics and hence the web page might not be considered as the atomic node. In this paper, the web page is partitioned into blocks using the visionbased page segmentation algorithm. By extracting the page-toblock, block-to-page relationships from link structure and page layout analysis, we can construct a semantic graph over the WWW such that each node exactly represents a single semantic topic. This graph can better describe the semantic structure of the web. Based on block-level link analysis, we proposed two new algorithms, Block Level PageRank and Block Level HITS, whose performances we study extensively using web data. Categories and Subject Descriptors H.3.3 [Information Storage and Retriev...
Deng Cai, Xiaofei He, Ji-Rong Wen, Wei-Ying Ma
Added 30 Jun 2010
Updated 30 Jun 2010
Type Conference
Year 2004
Where SIGIR
Authors Deng Cai, Xiaofei He, Ji-Rong Wen, Wei-Ying Ma
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