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Title: Web Page Ranking Solution Through sNorm (P) Algorithm Implementation
Authors: Kumar, Munish
Supervisor: Kumar, Ravinder
Keywords: Search Engine;Page Rank;Hyperlink;HUBAVG;SALSA
Issue Date: 23-Sep-2008
Abstract: Ranking has always been an important component for information retrieval system. The web is a massive collection of static and dynamic pages. It is an infinite source of information which includes countless hyperlinks. The collection of information provides a rich and unprecedented information retrieval source. Search Engine database contains the bulk of web pages so ranking of web page is essential for fulfill the user needs. Page Rank Linking is used to measure the importance and behavior of web page. The PageRank algorithm, which is a technique used to improve the relevance of results returned by search engine graph structure. Page Rank Algorithem calculates the rank of individual web page and Hypertext Induced Topic Search (HITS) depends upon the hubs and authority framework. A fast and efficient page ranking mechanism for web retrieval remains as a challenge. Several web page ranking algorithms Hypertext Induced Topic Search (HITS) and Page Rank have been proposed. Ranking has always been an important component of any information retrieval system. In the case of Web search its importance becomes critical. Due to the size of the Web, it is imperative to have ranking functions that capture the user needs. To this end the Web offers a rich context of information which is expressed through the hyperlinks In thesis the analysis of the importance of Web Page by using ranking algorithms is done and has proposed the new sNorm (p) Ranking algorithm. And its quality has been compared with existing algorithms like Hypertext Induced Topic Search (HITS), Stochastic Approach for Link-Structure Analysis (SALSA) and Norm (p). The algorithms are tested over multiple hyperlinks graph. Keywords: Search Engine, Page Rank, HITS, Hyperlink, SALSA, HUBAVG, sNorm(p), Graph.
Description: M.E. (CSED)
Appears in Collections:Masters Theses@CSED

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