2006Unpublished venueRequires access

Improving the Ranking Capability of the Hyperlink Based Search Engines using Heuristic Approach

Haider Ali Ramadhan, Khalil Shihab

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Abstract

To evaluate the informative content of a Web page, the Web structure has to be carefully analyzed. Hyperlink analysis, which is capable of measuring the potential information contained in a Web page with respect to the Web space, is gaining more attention. The links to and from Web pages are an important resource that has largely gone unused in existing search engines. Web pages differ from general text in that they possess external and internal structure. The Web links between documents can provide useful information in finding pages for a given set of topics. Making use of the Web link information would allow the construction of more powerful tools for answering user queries. Google has been among the first search engines to utilize hyper links in page ranking. Still two main flaws in Google need to be tackled. First, all the backlinks to a page are assigned equal weights. Second, less content rich pages, such as intermediate and transient pages, are not differentiated from more content rich pages. To overcome these pitfalls, this paper proposes a heuristic based solution to differentiate the significance of various backlinks by assigning a different weight factor to them depending on their location in the directory tree of the Web space

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What this paper is about

To evaluate the informative content of a Web page, the Web structure has to be carefully analyzed. Hyperlink analysis, which is capable of measuring the potential information contained in a Web page with respect to the Web space, is gaining more attention. The links to and from Web pages are an important resource that has largely gone unused in existing search engines. Web pages differ from general text in that they possess external and internal structure. The Web links between documents can provide useful information in finding pages for a given set of topics. Making use of the Web link information would allow the construction of more powerful tools for answering user queries. Google has been among the first search engines to utilize hyper links in page ranking. Still two main flaws in Google need to be tackled. First, all the backlinks to a page are assigned equal weights. Second, less content rich pages, such as intermediate and transient pages, are not differentiated from more content rich pages. To overcome these pitfalls, this paper proposes a heuristic based solution to differentiate the significance of various backlinks by assigning a different weight factor to them depending on their location in the directory tree of the Web space

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Available abstract

To evaluate the informative content of a Web page, the Web structure has to be carefully analyzed. Hyperlink analysis, which is capable of measuring the potential information contained in a Web page with respect to the Web space, is gaining more attention. The links to and from Web pages are an important resource that has largely gone unused in existing search engines. Web pages differ from general text in that they possess external and internal structure. The Web links between documents can provide useful information in finding pages for a given set of topics. Making use of the Web link information would allow the construction of more powerful tools for answering user queries. Google has been among the first search engines to utilize hyper links in page ranking. Still two main flaws in Google need to be tackled. First, all the backlinks to a page are assigned equal weights. Second, less content rich pages, such as intermediate and transient pages, are not differentiated from more content rich pages. To overcome these pitfalls, this paper proposes a heuristic based solution to differentiate the significance of various backlinks by assigning a different weight factor to them depending on their location in the directory tree of the Web space

Key concepts: Computer science, Web page, Information retrieval, Backlink, Static web page, World Wide Web, Hyperlink, Web search engine

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