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- W2145725307 abstract "The large volume of unstructured text data available at various sources such as digital libraries, news, internet, has given arise a need to organize the information as per the user's requirement. Search for relevant information is efficient when context of the selected word in the document is considered. Document Clustering aims to discover natural groupings, and present an overview of classes (topics) in a document collection. Thus, documents with similar contents are related to the same query. In this paper, a new method for clustering documents is proposed. In the proposed method, the term frequency of the document collection is computed and contexts based terms are fused. Agglomerative clustering and Bisecting K-Means are used to cluster the extracted features. General Terms Clustering, Algorithms" @default.
- W2145725307 created "2016-06-24" @default.
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- W2145725307 date "2013-06-26" @default.
- W2145725307 modified "2023-09-30" @default.
- W2145725307 title "Using Data Fusion for a Context Aware Document Clustering" @default.
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- W2145725307 doi "https://doi.org/10.5120/12497-7430" @default.
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