期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2013
卷号：4
期号：3
页码：557-560
语种：English
出版社：Ayushmaan Technologies
摘要：The data generated by conventional categorical data clustering is incomplete because the information provided is also incomplete. This project presents a new link-based approach, which improves the categorical clustering by discovering unknown entries through similarity between clusters in an ensemble. A graph partitioning technique is applied to a weighted bipartite graph to obtain the final clustering result. It plays a crucial, foundation role in machine learning, data mining, information retrieval and pattern recognition. The experimental results on multiple real data sets suggest that the proposed link-based method almost always outperforms both conventional clustering algorithms for categorical data and well-known cluster ensemble technique. This paper proposing an Algorithm called Weighted Triple- Quality (WTQ), which also uses k-means algorithm for basic clustering To introduce a minhash algorithm to avoid the data duplication in different cluster and also Secure Information Retrieval (SIR )data from the final cluster ensemble result.
