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Title:
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AN APPROACH TO DOCUMENT CLUSTERING USING HYBRID METHOD |
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Author(s):
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Goran imi?, Ejub Kajan, Zoran Jeremi?, Dragan Randjelovi? |
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ISBN:
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978-972-8939-67-0 |
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Editors:
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Piet Kommers and Pedro Isaías |
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Year:
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2012 |
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Edition:
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Single |
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Keywords:
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E-Government, Document clustering, Fuzzy C mean algorithm, Cosine similarity |
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Type:
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Full Paper |
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First Page:
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153 |
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Last Page:
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159 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This paper deals with e-government documents multilayered clustering based on hybrid approach that combines Fuzzy-C-mean algorithm, cosine similarity and semantic similarity measures. The system described here is intended to reduce response time between citizens questions and government answers, either to eliminate or to minimize the role of subject matter experts. Layers of documents are defined by key terms that are discovered by a clustering engine that we named ADVANSE. After short overview of clustering algorithms the paper concentrates step by step on the functionality of ADVANSE. Finally, concluding remarks emphasize some important features of this approach and gave future research directions. |
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