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In this paper we present a new video object trajectory clustering algorithm, which allows us to model and analyse the patterns of object behaviors based on the extracted features using tensor analysis. The proposed algorithm consists of three steps as follows: extraction of trajectory features by tensor analysis, non-parametric probabilistic mean shift clustering and clustering correction. The performance...
A novel approach based on the probabilistic latent semantic analysis model (pLSA) for automatic musical genre classification is proposed in this paper. Unlike traditional usage, the pLSA is used to model musical genre instead of single music signal in the proposed approach. First, an unsupervised clustering algorithm is utilized to group temporal segments in music signals into several natural clusters...
In pervasive computing environment, more personalized information can be achieved, and better user profile model can be built, thus personalized service can be realized. User profile is the critical aspect in personalized service of digital library. This paper proposes structure and mechanism of user profile in personalized service of digital library. The main problems during its construction are...
A novel approach to construct accurate and interpretable high-dimensional fuzzy classification system is proposed in this paper. First, in order to relieve the problem of dimension disaster, a feature selection is accomplished by the Simba algorithm. Then a fuzzy clustering algorithm is using to identify an initial fuzzy system. Finally the structure and parameters of the fuzzy system are optimized...
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