Enhancing Document Clustering Using Term Re-weighting Based on Semantic Features
نویسندگان
چکیده
منابع مشابه
Document Clustering Using Term Weights and Class Label Terms Based on Semantic Features
Clustering of class labels can be generated automatically, which is much lower quality than labels specified by human. In this paper, we propose a new enhancing document clustering method using terms of class label and term weights. The terms of class label can well represent the inherent structure of document clusters by non-negative matrix factorization (NMF). It can also improve the quality ...
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Different document representation models have been proposed to measure semantic similarity between documents using corpus statistics. Some of these models explicitly estimate semantic similarity based on measures of correlations between terms, while others apply dimension reduction techniques to obtain latent representation of concepts. This paper proposes new hybrid models that combine explici...
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Measuring inter-document similarity is one of the most essential steps in text document clustering. Traditional methods rely on representing text documents using the simple Bag-of-Words (BOW) model which assumes that terms of a text document are independent of each other. Such single term analysis of the text completely ignores the underlying (semantic) structure of a document. In the literatur...
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ژورنال
عنوان ژورنال: The Journal of the Korean Institute of Information and Communication Engineering
سال: 2013
ISSN: 2234-4772
DOI: 10.6109/jkiice.2013.17.2.347