Agent based weighted page ranking algorithm for Web content information retrieval

V. Nagappan, P. Elango
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引用次数: 15

Abstract

The rapid extension of the web is causing the constant growth of information, important to several problems such as an increased difficulty of extracting potentially useful Information. Search engines have become the most powerful tools for obtaining useful information scattered on the web. Web content mining goads this problem with the help of agent by retrieving explicit information from different web sites for its access and knowledge discovery. Most of the search engines are ranking their search results in response to users queries to make their search navigation easier. This paper also explores agent based weighted page ranking algorithms for web content mining to retrieve more relevant information. The proposed extended Page Rank algorithm is Agent based Weighted Page Rank Algorithm. The Agent assigns larger rank values to more important pages instead of dividing the rank value of a page evenly among its content. AWPR algorithm retrieve the most important content information or web pages in front of end users.
基于Agent的Web内容信息检索加权页面排序算法
网络的快速扩展导致了信息的不断增长,这对一些问题很重要,比如提取潜在有用信息的难度增加。搜索引擎已经成为获取分散在网络上的有用信息的最强大的工具。Web内容挖掘在agent的帮助下解决了这一问题,agent从不同的Web站点中检索明确的信息,供其访问和知识发现。大多数搜索引擎都根据用户的查询对搜索结果进行排序,以使搜索导航更容易。本文还探讨了基于代理的网页权重排序算法,用于网页内容挖掘,以检索更多的相关信息。本文提出的扩展页面排名算法是基于Agent的加权页面排名算法。Agent将较大的rank值分配给更重要的页面,而不是将页面的rank值平均分配给其内容。AWPR算法在最终用户面前检索最重要的内容信息或网页。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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