文章基本信息

标题：Grouping of Personalized Web Documents by Naming Aliases
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作者：S. S. Shinde ; P. R. Devale
期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：9
出版社：S.S. Mishra
摘要：In lots of works such as information retrieval, sentiment analysis, person name disambiguation as well as in biomedical fields it is required to identify the accurate references to an entity among a list of references. More previous work had been done on solving lexical ambiguity. Here we proposed a method that is based on referential ambiguity. In this paper we proposed a method which is based on referential ambiguity to extract correct alias for a given name. Given a person name and / or with context data such as location, organization retrieves top K snippets and depth up to level two from a web search engine. With the help of lexical pattern extract candidate aliases. To find correct alias from a list of aliases we used n-depth crawling method. This method is useful to improve the precision and minimize the recall than the previous baseline method. Using these candidate aliases related personalized web documents are clustered or grouped. Grouping attains high accuracy and reduces the complexity
关键词：Web mining; information retrieval; n-depth crawling; clustering; and web text analysis