Abstract
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.
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Romero, F.P., Soto, A., Olivas, J.A. (2007). A Hybrid Model for Document Clustering Based on a Fuzzy Approach of Synonymy and Polysemy. In: Castillo, O., Melin, P., Ross, O.M., Sepúlveda Cruz, R., Pedrycz, W., Kacprzyk, J. (eds) Theoretical Advances and Applications of Fuzzy Logic and Soft Computing. Advances in Soft Computing, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72434-6_18
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DOI: https://doi.org/10.1007/978-3-540-72434-6_18
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