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A General Fuzzy-Based Framework for Text Representation and Its Application to Text Categorization

机译:基于模糊的通用文本表示框架及其在文本分类中的应用

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In this paper we develop the general framework for text representation based on fuzzy set theory. This work is extended from our original ideas [5],[4], in which a document is represented by a set of fuzzy concepts. The importance degree of these fuzzy concepts characterize the semantics of documents and can be calculated by a specified aggregation function of index terms. Based on this representation, a general framework is proposed and applied to text categorization problem. An algorithm is given in detail for choosing fuzzy concepts. Experiments on the real-world data set show that the proposed method is superior to the conventional method for text representation in text categorization.
机译:在本文中,我们基于模糊集理论开发了文本表示的通用框架。这项工作是从我们最初的想法[5],[4]扩展而来的,在该想法中,文档由一组模糊概念表示。这些模糊概念的重要性程度表征了文档的语义,可以通过指定的索引词聚合函数来计算。基于这种表示,提出了一个通用框架并将其应用于文本分类问题。详细给出了用于选择模糊概念的算法。在真实数据集上的实验表明,该方法在文本分类中优于传统的文本表示方法。

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