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bat-Grey Wolf Optimizer and kernel mapping for automatic incremental clustering

International Journal of Modeling, Simulation, and Scientific Computing 2020年第4期11卷 154-176页

作者： C.Vidyadhari N.Sandhya P.Premchand Computer Science and Engineering Department JNTUK KakinadaIndia Computer Science and Engineering Department VNRVJIET HyderabadIndia Computer Science and Engineering Department University College of Engineering Osmania University HyderabadIndia

The technical advancement in information systems contributes towards the massive availability of the documents stored in the electronic databases such as e-mails,internet and web ***,it becomes a complex task for arranging and browsing the required *** paper proposes an approach for incremental clustering using the batGrey Wolf Optimizer(BAGWO).The input documents are initially subjected to the pre-processing module to obtain useful keywords,and then the feature extraction is performed based on wordnet *** feature extraction,feature selection is carried out using entropy ***,the clustering is done using the proposed BAGWO *** BAGWO algorithm is designed by integrating the bat Algorithm(BA)and Grey Wolf Optimizer(GWO)for generating the different clusters of text ***,the clustering is determined using the BAGWO algorithm,yielding the group of *** the other side,upon the arrival of a new document,the same steps of pre-processing and feature extraction are *** on the features of the test document,the mapping is done between the features of the test document,and the clusters obtained by the proposed BAGWO *** mapping is performed using the kernel-based deep point distance and once the mapping terminated,the representatives are updated based on the fuzzy-based representative *** performance of the developed BAGWO outperformed the existing techniques in terms of clustering accuracy,Jaccard coefficient,and rand coefficient with maximal values 0.948,0.968,and 0.969,respectively.

关键词： Incremental clustering Grey Wolf Optimizer bat optimization fuzzy concept kernel-based deep point distance.

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