Evaluation of Clustering Algorithm in Data Mining
Keywords:
Cluster Algorithm, Data Mining, bisecting k-means, FIHC, CFWS find CFWMSAbstract
Text mining is the use of data mining techniques to unstructured text in order to extract important and nontrivial knowledge. One of the key methods of text mining, or the unsupervised classification of related content into various categories, is text clustering. The performance of text clustering is being improved in this study. We looked on four areas of the text clustering algorithms: document representation, document similarity analysis, high dimension reduction, and parallelization. We suggest a collection of very effective text clustering techniques that focus on the special features of unstructured text databases. All of the suggested algorithms have undergone thorough performance studies. We contrasted these techniques with current text clustering algorithms in order to assess their performance.
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