Ontology based Fuzzy Classification of Web Documents for Semantic Information Retrieval

被引：0

作者：

Joshi, Kajal ^{[1
,2
]}

Verma, Ashish ^{[2
]}

Kandpal, Ankita ^{[1
]}

Garg, Shalini ^{[1
]}

Chauhan, Rashmi ^{[1
,2
]}

Goudar, R. H. ^{[2
]}

机构：

[1] GEU Dehradun, Dept Informat Technol, Dehra Dun, India

[2] GEU Dehradun, Dept Comp Sci & Engn, Dehra Dun, India

来源：

2013 SIXTH INTERNATIONAL CONFERENCE ON CONTEMPORARY COMPUTING (IC3) | 2013年

关键词：

Information Retrieval; Ontology; Semantic search; Query Expansion; K-means clustering; Fuzzy Sets;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Several approaches have been introduced in the field of information retrieval. Although these approaches are effective but sometimes they are not able to provide accurate information to the user. In this paper an ontology based approach of information retrieval has been presented that uses fuzzy set of various documents for a specific domain. An algorithm for fuzzy based classification of web documents is proposed to create semantic index. The proposed algorithm differs from others as: it utilizes K-means clustering algorithm to find semantically similar terms and domain ontology as well. The retrieved results would always be semantic as they are limited to a particular threshold of classified range.

引用

页码：1 / 5

页数：5

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