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Experiments are carried out on datasets with different dimensions selected from UCI datasets by using two classical clustering algorithms. The results of the experiments indicate that when the dimensionality of the real dataset is less than or equal to 30, the clustering algorithms based on distance are effective. For high-dimensional datasets--dimensionality is greater than 30, the clustering algorithms...
In this paper, the necessity of ranking of the enterprise's informatization capacity maturity is researched on the basis of EICMM (Enterprise Informatization Capacity Maturity Model). Based on the EICMM, we adopt the proper method (Cluster Analytical Method) for the empirical research, commence from the evaluated index system, design the questionnaires and collect the related data of informatization,...
A clustering based composite kernels support vector machine ensemble forecasting model is proposed for the chaotic time series prediction. First, fuzzy possibility c-mean clustering algorithm (FPCM) is adopted to partition the input dataset into several subsets, which can overcome the drawback caused by outlier and noise in conventional fuzzy c-mean method. Then, SVMs with composite kernels that best...
Query expansion (QE) is one of the most important mechanisms in the information retrieval field. A typical QE method usually redefines the query with related terms. These techniques suffer from retrieval performance degradation due to imprecise choice of query's additive terms in the QE process. Semantic expansion is proposed to improve query precision, while the expansion concept is hard to be obtained...
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