Applications of MVS on Hierarchical Clustering Algorithms

Provided by: Creative Commons
Topic: Data Management
Format: PDF
Clustering is a valuable method that arranges a large quantity of unordered text documents into a small number of expressive and coherent clusters, thereby offering a basis for instinctive and informative steering and browsing mechanisms. There are some clustering methods which have to adopt 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 main difference between a traditional dissimilarity/similarity measure and ours is that the former uses only a only a single lookout, which is the origin, while the latter utilizes many diverse viewpoints, which are objects assumed to not be in the same cluster with the two objects being measured.

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