一种基于领域知识的网页动态聚类方法

T. D’abreo, A. Khandare, P. Janrao
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引用次数: 0

摘要

普通网页推荐系统推荐的网页被列出,而不是聚类。网络搜索是基于关键词的。搜索引擎不理解搜索查询的含义,因为它没有搜索查询的背景领域知识。早期的搜索引擎根据形成的静态聚类对网页进行聚类[2]。由于静态集群在映射Web页面时面临一些缺点,因此需要找到解决方案。为了高效聚类,本文提出了一种考虑域的动态聚类方案。数据挖掘,基于语义的挖掘,推荐系统,聚类技术。
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A Novel Approach to Cluster Web Pages Dynamically based on Domain Knowledge
Web Pages which are recommended by the normal web page recommendation system are listed and are not clustered. The web search is based on keyword. The search engine does not understand the meaning of the searched query as it does not have a background domain knowledge of the searched query. The earlier search engine designed clustered the web pages according to static clusters formed [2]. As static clustering, faced some drawbacks of mapping the Web pages, there was a need to find the solution for the same. This paper presents a solution to form the clusters dynamically considering the domains for efficient clustering. General Terms Data mining, Semantic-based Mining, Recommendation Systems, Clustering techniques.
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