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DC FieldValueLanguage
dc.contributorDepartment of Computingen_US
dc.creatorChoi, Kam-chang-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/5648-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleWeb crawling : duplication and freshness of web pagesen_US
dcterms.abstractThis dissertation studies challenges and issues faced in the implementation of Web crawler. A crawler is a system which retrieves web pages from the Web, stores the pages locally to serve different proposes, for a Web search engine indexing, building digital library and so on. A crawler usually downloads hundreds of millions, or even billions, pages in a short period and is responsible for keeping downloaded pages up-to-date. In addition, the crawler has the reasonability to avoid downloading duplicated pages to make sure the limited resource is being best used as well. This dissertation studies how we can build an effective Web crawler which uses as little resource as possible to retrieve "high quality" pages, and maintain pages collection quality, up-to-date and higher value. In order to achieve these goals, we firstly identify common definitions of "(near) duplication", "freshness" of pages, and study mathematical function on quality metrics "freshness" and "age" of pages. We shall discuss topics and technologies closely related to page duplication detection, the web site mirroring detection and URL normalization too. I then propose a data structure and associated algorithms to speed up duplication detection process, at the same time they reduce "false-positive" chance. On the hand, I make recommendation to improve page revisiting policy based on reducing number of pages by duplication detection. I have done three experiments on the suggested data structure and algorithms. Finally, I conclude the dissertation with findings of experiments and suggesting a robust integrated architecture for duplication detection and page revisiting.en_US
dcterms.extentvii, 156 leaves : ill. ; 31 cm.en_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2010en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.Sc.en_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.LCSHWeb search engines.en_US
dcterms.LCSHData mining -- Quality control.en_US
dcterms.LCSHWeb sites -- Designen_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/5648