Hierarchical Bisecting Clustering with Multi View-Point Based Similarity Measure

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Provided by: International forum of researchers Students and Academician
Topic: Big Data
Format: PDF
Clustering is a useful technique that organizes a large quantity of unordered text documents into a small number of meaningful and coherent clusters, thereby providing a basis for intuitive and informative navigation and browsing mechanisms. There are some clustering methods which have to assume some cluster relationship among the data objects that they are applied on. Similarity between a pair of objects can be defined either explicitly or implicitly. The major difference between a traditional dissimilarity/similarity measure and ours is that the former uses only a only a single viewpoint, which is the origin, while the latter utilizes many different viewpoints, which are objects assumed to not be in the same cluster with the two objects being measured.
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