An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for const...
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ISBN:
(纸本)1581139128
An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for constructing the semantic link network. The basic premise of this work is that the semantics of a web page can be reflected by a set of keywords, and the semantic relationship between two web pages can be determined by the semantic relationship between their keyword sets. The approach adopts the data mining algorithms to discover the semantic relationships between keyword sets, and then uses deductive and analogical reasoning to enrich the semantic relationships. The proposed algorithms have been implemented. Experiment shows that the approach is feasible.
The future Web can be imagined as a life network consisting of resource nodes and semantic relationship links between them. Any node has a life span from birth -?adding it to the network -?to death -?removing it from ...
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ISBN:
(纸本)1581139128
The future Web can be imagined as a life network consisting of resource nodes and semantic relationship links between them. Any node has a life span from birth -?adding it to the network -?to death -?removing it from the network. Through establishing and investigating two types of models for such a network, we obtain the same scale free distribution of semantic links. Simulations and comparisons validate the rationality of the proposed models.
This paper concerns a greedy EM algorithm for t-mixture modeling, which is more robust than Gaussian mixture modeling when a typical points exist or the set of data has heavy tail. Local Kullback divergence is used to...
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This paper concerns a greedy EM algorithm for t-mixture modeling, which is more robust than Gaussian mixture modeling when a typical points exist or the set of data has heavy tail. Local Kullback divergence is used to determine how to insert new component. The greedy algorithm obviates the complicated initialization. The results are comparable to that of split-and-merge EM algorithm while the proposed algorithm is faster. Also the by product of a sequence of mixture models is useful for model selection. Experiments of synthetic data clustering and unsupervised color image segmentation are given.
Rough set theory is emerging as a new tool for dealing with fuzzy and uncertain data. In recent years, it has been successfully applied in such fields as machine learning, data mining, knowledge acquiring, etc. In thi...
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Stereo matching is one of the most active research areas in computer vision. In this paper, a fast stereo matching algorithm by means of epipolar constraint and multiresolution approach was presented. The searching sc...
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Stereo matching is one of the most active research areas in computer vision. In this paper, a fast stereo matching algorithm by means of epipolar constraint and multiresolution approach was presented. The searching scope of corresponding pixels in the original image is obtained and has diminished a lot based on multiresolution approach. Then intensity correlation principle and epipolar constraint can be applied to get the stereo matching results in this scope. In this way, we reduce the search time for correspondence and ensure the validity of matching. The experimental results show this algorithm is effective and efficient.
This paper proposes a new fast recursive total least squares (N-RTLS) algorithm to recursively compute the TLS solution for adaptive finite impulse response (FIR) filtering. The N-RTLS algorithm is based on the minimi...
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Multivariate t-mixture modelling is more robust than Gaussian mixture modelling to a set of data containing a group or groups of observations with longer than Gaussian tails or a typical observations. To alleviate the...
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ISBN:
(纸本)0780384032
Multivariate t-mixture modelling is more robust than Gaussian mixture modelling to a set of data containing a group or groups of observations with longer than Gaussian tails or a typical observations. To alleviate the problem of local convergence of the traditional EM algorithm, a split-and-merge operation is introduced into the EM algorithm for multivariate t-mixtures. The split-and-merge equations are first presented theoretically and then a new merge method is acquired. Accordingly, a modified EM algorithm is constructed. Experiments of data clustering and unsupervised color image segmentation are given.
More researchers recognize that it is an emergent and important issue that intelligent tutoring mechanism can be depicted, evaluated and measured on the uniform theoretical foundation which should be a highly formaliz...
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Digital Human is a booming research area andits combination with distance education will greatlypromote the advances of medicine, anatomy andother relevant disciplines, ht this paper they areintegrated to establish a...
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ISBN:
(纸本)0780379411
Digital Human is a booming research area andits combination with distance education will greatlypromote the advances of medicine, anatomy andother relevant disciplines, ht this paper they areintegrated to establish a local-network baseddistance education experimental system whichcontains functions such as teaching, practicing,tutoring and discussing, etc. The volume of thedigital human datasets is too huge to be dealt withtraditional centralized storing methods, so the gridtechnology is introduced to provide an efficient, safeand transparent management of the mass *** this experiment our solution is proved tobe valid and feasible.
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