Personalized Web Search Using WebClickSVD
Abstract— Personalized Web Search Using WebClickSVD.This paper is focused on computing importance of a web page in an efficient way. Web page ranking is an essential factor in web search. Many modules and algorithms have been proposed using different resources with different assumptions. The algorithms proposed include Page Rank, Browse Rank, Browse Rank Plus, HITS and many more. Page Rank focuses on ranking a page based on the number of inlinks and outlinks to a page. Whereas Browse Rank focuses on ranking the page based on the value it provides to the user. Several other algorithms have been proposed since, that focuses only on one or two particular factors. This paper proposes ranking a page based on multiple factors that includes reachability, value and user feedback. The major aim is to rank a web page based on these < Final Year Projects >three crucial factors rather than considering one or two factors taken into account by existing methodologies. Every user has a different and unique background and a particular aim when searching for information on the Web. Web search personalization is mainly aimed at tailoring search results to a specific user based on that user’s interests and preferences. Major challenges that effective personalized search is affected with includes accurately identifying the user context and organizing the information in such a way that it matches the particular context. An effective mechanism is employed to personalize the search and also to rank the page based on multiple factors.
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