A BI-Partite Graph Partition and Link Based Approach for Solving Categorical Data Clustering

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Provided by: International Journal of Engineering Trends and Technology
Topic: Big Data
Format: PDF
Link based approach to solve the problem of categorical data clustering through cluster ensembles. It consists of generating a set of clustering from the dataset and combining them into a final clustering. The combination process is to improve the quality of individual data clustering. The ensemble information matrix presents only cluster data point relation with many entries being left unknown. Link based approach discovering unknown entries through similarity between clusters. Similarity approach is applied to weighted bipartite graph to obtain final clustering. In this paper propose a Weighted Triple Quality (WTQ),which is provide efficient approximation of the similarity between clusters.
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