首页> 外文会议>IFSA(International Fuzzy Systems Association); 2007; >A Hybrid Model for Document Clustering Based on a Fuzzy Approach of Synonymy and Polysemy
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A Hybrid Model for Document Clustering Based on a Fuzzy Approach of Synonymy and Polysemy

机译:基于同义和多义模糊方法的文档聚类混合模型

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A new model for document clustering is proposed in order to manage with conceptual aspects. To measure the presence degree of a concept in a document (or even in a document collection), a concept frequency formula is introduced. This formula is based on new fuzzy formulas to calculate the synonymy and polysemy degrees between terms. To solve the several shortcomings of classical clustering algorithm a soft approach to hybrid model is proposed. The clustering procedure is implemented by two connected and tailored algorithms with the aim to build a fuzzy-hierarchical structure. A fuzzy hierarchical clustering algorithm is used to determine an initial clustering and the process is completed using an improved soft clustering algorithm. Experiments show that using this model, clustering tends to perform better than the classical approach.
机译:提出了一种用于文档聚类的新模型,以便在概念方面进行管理。为了测量概念在文档中(甚至在文档集合中)的存在程度,引入了概念频率公式。该公式基于新的模糊公式来计算术语之间的同义词和多义度。为了解决经典聚类算法的几个缺点,提出了一种软的混合模型方法。聚类过程由两个相互连接且量身定制的算法实现,目的是建立模糊层次结构。模糊层次聚类算法用于确定初始聚类,并使用改进的软聚类算法完成该过程。实验表明,使用这种模型,聚类的性能往往优于传统方法。

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