文章基本信息

标题：Web Search Result Clustering using IFCWR Algorithm
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作者：Arun Kumar Pal ; Ashwini Londhe ; Nitin Patil 等
期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2016
卷号：5
期号：3
页码：15991-15995
DOI：10.18535/ijecs/v5i3.19
出版社：IJECS
摘要：In the modern age of Internet, usage of social media is growing rapidly on internet, organizing the data, interpreting andsupervising User generated content (UGC) has become one of the major concerns. Updating new topics on internet is not a big task butsearching topics on the web from a vast volume of UGC is one of the major challenges in the society. In this paper we deal with web searchresult clustering for improving the search result returned by the search engines. However there are several algorithms that already existsuch as Lingo, K-means etc. In this paper basically we work on descriptive-centric algorithm for web search result clustering called IFCWRalgorithm. Maximum numbers of clusters are randomly selected by using Forgy’s strategy, and it iteratively merges clusters until mostrelevant results are obtained. Every merge operation executes Fuzzy C-means algorithm for web search result clustering. In Fuzzy C-means,clusters are merged based on cosine similarity and create a new solution (current solution) with this new configuration of centroids. In thispaper we investigate the Fuzzy C-means algorithm, performing pre-processing of search query algorithm and try to giving the best solution
关键词：Iterative Fuzzy C-means; IFCWR; Query pre-processing algorithm; Porters Stemming algorithm