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On-line topical importance estimation:an effective focused crawling algorithm combining link and content analysis

Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第8期10卷 1114-1124页

作者： Can WANG Zi-yu GUAN Chun CHEN Jia-jun BU Jun-feng WANG Huai-zhong LIN School of Computer Science and Technology Zhejiang University Hangzhou 310027 China

focused crawling is an important technique for topical resource discovery on the *** key issue in focused crawling is to prioritize uncrawled uniform resource locators(URLs) in the frontier to focus the crawling on relevant *** focused crawlers mainly rely on content ***-based techniques are not effectively exploited despite their *** this paper,we propose a new frontier prioritizing algorithm,namely the on-line topical importance estimation(OTIE) *** combines link-and content-based analysis to evaluate the priority of an uncrawled URL in the *** performed real crawling experiments over 30 topics selected from the Open Directory Project(ODP) and compared harvest rate and target recall of the four crawling algorithms:breadth-first,link-context-prediction,on-line page importance computation(OPIC) and our *** results showed that OTIE significantly outperforms the other three algorithms on the average target recall while maintaining an acceptable harvest ***,OTIE is much faster than the traditional focused crawling algorithm.

关键词： focused crawlers Topical crawlers PageRank Classifiers On-line topical importance estimation (OTIE) algorithm

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A New Framework for focused Web Crawling

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Wuhan University Journal of Natural Sciences 2006年第5期11卷 1394-1397页

作者： PENG Tao HE Fengling ZUO Wanli College of Computer Science and Technology/KeyLaboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changehun130012 Jilin China

focused crawlers are important tools to support applications such as specialized Web portals, online searching, and Web search engines. A topic driven crawler chooses the best URLs and relevant pages to pursue during Web crawling. It is difficult to deal with irrelevant pages. This paper presents a novel focused crawler framework. In our focused crawler, we propose a method to overcome some of the limitations of dealing with the irrelevant pages. We also introduce the implementation of our focused crawler and present some important metrics and an evaluation function for ranking pages relevance. The experimental result shows that our crawler can obtain more ＂important＂ pages and has a high precision and recall value.

关键词： focused crawlers irrelevant pages relevance metrics

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