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In this paper we present a novel clustering analysis method based on the Most Similar Relation Diagram (MSRD). MSRD is a diagram in which each datum of a dataset is linked to its most similar data. By cutting off some links in the diagram a certain number of clusters are formed. A compare of the MSRD method with hierarchical method is implemented.(More)
In this paper a new method is presented and used in clustering document collections. This method is based on the one-dimensional arrays of Self-Organizing Map network (1-D SOM array). The main idea of this method is to obtain the clustering results by calculating the distances between every two adjacent MSPs (the most similar prototype to the input vector )(More)
The MSRD (Most Similar Relation Diagram) of a dataset is a weighted undirected graph constructed from an initial dataset. In the MSRD, each datum represented by a vertex, is connected with its MSD (Most Similar Data), and each MSRG (Most Similar Relation Group), represented by a sub-graph, is connected with its MSG (most similar group) through connecting(More)
—In this paper, based on differential characteristic set algorithm of a differential polynomial system, an algorithm for calculating two kinds of approximate symmetries of a perturbed partial differential equation is suggested. The difficulty of solving determining equations of the approximate symmetries is overcome significantly by the algorithm. As(More)
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