The Research Of Improvement In Link-based Pagerank Sorting Algorithm

Search Engine technology is developed with the situation of growing computing resources and computing ability in all Fields Currently, the algorithm of PageRank which based on link analysis is the essential part of it. The purpose of sorting the web pages which have been searched by importance is to make the web pages which conforms the need of user stand in front of the other web pages. Because of limitation and objectivity of the traditional sorting algorithm, the searching index is not perfectly in specific field. So the searching result usually deviate from the requirement of the user and it is difficult to satisfy the need of diversification and personalization of searching. A perfect index system should be able to discriminate and classify the specific field of searching, improve the sorting algorithm for specific user's requirement and resource characteristics in the original sorting technology foundation.This article discusses Search Engine and basic concepts of PageRank, summarizes the characteristics of the index in different fields, analyzes different kinds of models, and establishes a high comprehensive indexing mechanism. It details the principle of PageRank algorithm, analyzes the shortcomings of existing link analysis algorithms and the searching problems in various fields, and then proposes the improving strategies. It describes the searching for a specific area, the improved PageRank algorithm model based on traditional algorithms. It gradually illustrate improved PageRank algorithm model that based on Topical Relevance, feedback of information release time and page themes blocking mechanism.This article prorose a comprehensive improvement model of PageRank. Through comparative analysis of the original algorithm, this algorithm is proved to be better in timeliness and relevance.