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One of the main preprocessing steps for having a high performance text classifier is feature weighting. Commonly used feature weighting methods such as TF and IDF-based methods only consider the distribution of a feature in the document(s) and do not consider class information for feature weighting. In this paper, we present TFCRF (Term Frequency and Category Relevancy Factor) method in which the...
Text categorization (TC) is an important component in many information organization and information management tasks. Two key issues in TC are feature coding and classifier design. The Euclidean distance is usually chosen as the similarity measure in K-nearest neighbor classification algorithm. All the features of each vector have different functions in describing samples. So we can decide different...
Text categorization is an important research field within text mining. The initial objective of text categorization is to recognize, understand and organize various volumes of texts or documents. The general procedures of categorization are treated as supervised learning, from which the similarity can be inferred from a collection of categorized texts for training purpose. Obviously, the typical approaches...
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