DocumentCode
2165402
Title
Fuzzy clustering of web documents using equivalence relations and fuzzy hierarchical clustering
Author
Kumar, Sudhakar ; Kathuria, Madhumita ; Gupta, Amit Kumar ; Rani, Meenu
Author_Institution
Dept. of Comput. Sci. & Eng., YMCA Univ. of Sci. & Technol., Faridabad, India
fYear
2012
fDate
5-7 Sept. 2012
Firstpage
1
Lastpage
5
Abstract
The conventional clustering algorithms have difficulties in handling the challenges posed by the collection of natural data which is often vague and uncertain. Fuzzy clustering methods have the potential to manage such situations efficiently. Fuzzy clustering method is offered to construct clusters with uncertain boundaries and allows that one object belongs to one or more clusters with some membership degree. In this paper, an algorithm and experimental results are presented for fuzzy clustering of web documents using equivalence relations and fuzzy hierarchical clustering.
Keywords
Internet; data mining; document handling; fuzzy logic; learning (artificial intelligence); pattern clustering; Web documents; Web mining; equivalence relations; fuzzy hierarchical clustering; uncertain boundaries; unsupervised learning; Algorithm design and analysis; Clustering algorithms; Clustering methods; Euclidean distance; Information retrieval; Web mining; Clustering; Document Clustering; Fuzzy Clustering; Information Retrieval; Search Engine; Web Mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering (CONSEG), 2012 CSI Sixth International Conference on
Conference_Location
Indore
Print_ISBN
978-1-4673-2174-7
Type
conf
DOI
10.1109/CONSEG.2012.6349496
Filename
6349496
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