Web Page Ranking Based on Text Substance of Linked Pages

World Wide Web is large sized repository of interlinked hypertext documents accessed via the Internet. Web may contain text, images, video, and other multimedia data. The user navigates through this using hyperlink. Search Engine gives millions of results and applies Web mining techniques to order the results. The sorted order of search results is obtained by applying some special algorithms called—Page ranking algorithms. The algorithm measures the importance of the pages by analyzing the number of inlinked and outlinked pages. Our proposed system is built on an idea that to rank the relevant pages higher in the retrieved document set, an analysis of both page‘s text substance and links information is required. The proposed approach is based on the assumption that the effective weight of a term in a page is computed by adding the weight of a term in the current page and additional weight of the term in the linked pages. In this chapter, we first study the nature of web pages, the various link analysis ranking algorithms and their limitations and then show the comparative analysis of the ranking scores obtained through these approaches with our new suggested ranking