In this paper, we investigate one-class and clustering problems by using statistical learning theory. To establish a universal framework, a unsupervised learning problem with predefined threshold η is formally descri...
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Web spider is a widely used approach to obtain information for search engines. As the size of the Web grows, it becomes a natural choice to parallelize the spider's crawling process. This paper presents a parallel...
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Feature extraction or selection is one of the most importmant steps in pattern recognition or pattern classification, data mining, machine learning and so on. In this paper, we introduce the information theory, propos...
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Based on Jordan curve theorem, a universal classification method based on hyper surface is recently put forward. The experiments show that the new method can efficiently and accurately classify large data size up to 1...
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Based on Jordan curve theorem, a universal classification method based on hyper surface is recently put forward. The experiments show that the new method can efficiently and accurately classify large data size up to 10/sup 7/ in three-dimensional space. However, the number of training samples needed to design a classifier grows with the dimension of the features. So a way to reduce the dimension of the features without losing any essential information is needed. We put forward a kind of simple and efficient dimension reduction method without losing any essential information to improve the performance of classification based on hyper surface for high dimension data.
Principal component analysis (PCA) is an important method in multivariate statistical analysis, and its main idea is compression of dimensionality including variables and samples. In this paper, based on the ideas con...
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A online infomax algorithm is proposed in this paper. The performances and properties of this online algorithm is investigated in detail. To the problem of the artifacts removal in real life EEG signal, both the onlin...
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The translation of inheritance nets to default logic has been discussed by Etherington[9],Touretzky[10],*** and inheritance nets are similar in some aspects and based on methods of translating inheritance nets to defa...
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The translation of inheritance nets to default logic has been discussed by Etherington[9],Touretzky[10],*** and inheritance nets are similar in some aspects and based on methods of translating inheritance nets to default logic,a translation of ontologies to default logic with a priority order on defaults is ***,properties of an ontology and the revision of ontologies can be studied in terms of default *** are assumed to be trees under the subsumption relation between concepts and have deduction rules to infer what are not explicitly *** statements in ontologies are translated to facts of default theories of the ontologies and the default inheritance of properties are represented by normal defaults with a priority order on them due to the intuition that subclasses overriding *** an ontology with a tree structure,it is consistent if and only if the default theory of the ontology has a unique extension.
This paper proposes a hierarchical iterative and self-supervised method (HISS) to acquire concept words from a large-scale, un-segmented Chinese corpus. It has two levels of iteration: the EM-CLS algorithm and the Vit...
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This paper proposes a hierarchical iterative and self-supervised method (HISS) to acquire concept words from a large-scale, un-segmented Chinese corpus. It has two levels of iteration: the EM-CLS algorithm and the Viterbi-C/S algorithm constitute the inner iteration for generating concept words, and the concept word validation constitutes the outer iteration together with the concept word generation. Through multiple iterations, it integrates the concept word generation and validation into a uniform acquisition process. In the process of acquisition, the HISS method can cope with the problem of over-segmentation, over-combination and data sparseness. The experimental result shows that the HISS method is valid for concept word acquisition that can simultaneously increase the precision and recall rate of concept word acquisition.
作者：
Hai ZhugeChina Knowledge Grid Research Group
Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China
In the human, society, interconnection environment and systems methodology perspectives, this paper answers the following questions: What are the Knowledge Grid and its distinguished features? What are its methodology...
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In the human, society, interconnection environment and systems methodology perspectives, this paper answers the following questions: What are the Knowledge Grid and its distinguished features? What are its methodology and major research issues? These answers are important to the development of this promising area.
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