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This paper proposed a new method of news summarization based on semantic similarity measure. It used Latent semantic indexing (LSI) to measure sentence similarity, then it used Singular Value Decomposition (SVD) to reduce the dimension of the word-sentence matrix, it used new clustering algorithm to cluster all the sentences. It ordered all the sentences according to their relevant positions in the...
In this paper, we extend our research to construct a system which provides clustering services, more than user-active search. We use DCT mapping to extract features from sequences, and discuss sequence similarities of whole similarity and partial similarity. The two kinds of similarity concepts will be applied when clustering sequences of equal-length and variable-length, respectively.In the case...
K-means clustering is widely used due to its fast convergence, but it is sensitive to the initial condition.Therefore, many methods of initializing K-means clustering have been proposed in the literatures. Compared with Kmeans clustering, a novel clustering algorithm called affinity propagation (AP clustering) has been developed by Frey and Dueck, which can produce a good set of cluster exemplars...
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