Kusum Kumari Bharti

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Dimension reduction is a well-known pre-processing step in the text clustering to remove irrelevant, redundant and noisy features without sacrificing performance of the underlying algorithm. Dimension reduction methods are primarily classified as feature selection (FS) methods and feature extraction (FE) methods. Though FS methods are robust against(More)
Due to fast growth of the internet technology there is need to establish security mechanism. So for achieving this objective NIDS is used. Datamining is one of the most effective techniques used for intrusion detection. This work evaluates the performance of unsupervised learning techniques over benchmark intrusion detection datasets. The model generation(More)
Text clustering is widely used for creating clusters of the digital documents. Selection of cluster centers plays an important role in creating clusters of the documents. In this paper, we use artificial bee colony algorithm (hereinafter referred to as ABC) to select an appropriate cluster centers for text documents. The ABC is a swarm intelligence based(More)