Intelligent web search system for personalised web search based on recommendation of web page communities

S. Chawla
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引用次数: 2

Abstract

In this paper an intelligent web search system is proposed based on recommendation of web page communities for personalised web search (PWS). Web page communities are set of web pages that provide the good quality resource on a given topic. The intelligent search system adapts the web search to the user's information need based on recommendation of web page communities. The groups of similar content clicked web pages in clusters are selected for generation of web page communities using maximum flow algorithm with hyperlink-induced topic search (HITS). The cluster of web page communities is selected for recommendations of relevant web pages to user during web search for effective web information retrieval. Experiment was conducted on collection of web query sessions in academics, entertainment and sports domain. The experimental results were compared with classic IR and PWS (HITS) based on same dataset and hence the results show the improvement in precision of search results using intelligent web search based on web page communities.
基于网页社区推荐的个性化网页搜索智能系统
本文提出了一种基于网页社区推荐的个性化网页搜索智能系统。Web页面社区是一组提供给定主题的高质量资源的Web页面。智能搜索系统基于网页社区的推荐,使网络搜索适应用户的信息需求。采用基于超链接诱导主题搜索(HITS)的最大流量算法,选取聚类中内容相似的网页组生成网页社区。在网页搜索过程中,选择网页社区集群向用户推荐相关网页,实现有效的网页信息检索。对学术、娱乐和体育领域的web查询会话进行了采集实验。将实验结果与基于相同数据集的经典IR和PWS (HITS)进行了比较,结果表明基于网页社区的智能web搜索提高了搜索结果的精度。
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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