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By researching all kinds of methods for document clustering, we put forward a new dynamic method based on genetic algorithm (GA). K-means is a greedy algorithm, which is sensitive to the choice of cluster center and very easily results in local optimization. Genetic algorithm is a global convergence algorithm, which can find the best cluster centers easily. Among the traditional document clustering...
This paper proposes a self-organized genetic algorithm for document clustering based on semantic similarity measure. The traditional method to represent text is that the document is organized as a string of words, while the conceptual similarity is ignored. We take advantage of thesaurus-based ontology to overcome this problem. To investigate how ontology method could be used effectively in document...
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