A New Hybrid Feature Selection using Natural Language Processing for Text Clustering
نویسندگان
چکیده
Text clustering is unsupervised machine learning method.It needs representation of objects and similarity measure. which compares distribution of features between objects. For the high dimensionality of feature space performance of clustering algorithms decreases.Two techniques are used to deal with this problem: feature extraction and feature selection.In this paper, we describe the hybrid method used for text clustering which is the combination of active feature selection,genetic algorithm and bisecting K-means.Internal quality measures computes the effectiveness of clustering.Our method is compared with K-means.
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