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Collaborating semantic link network with resource space model

4th International Conference on Grid and Cooperative computing - GCC 2005

作者： Xing, Yunpeng Liu, Jie Sun, Xiaoping Yao, Erlin Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate School Chinese Academy of Sciences Beijing China Hunan Knowledge Grid Lab. Hunan University of Science and Technology Hunan China

ISBN: (纸本)3540305106

The Semantic Link Network model SLN and Resource Space Model RSM are semantic models proposed separately for effectively specifying and managing versatile resources across the Internet. Collaborating the relational semantics of SLN with the classification semantics of the RSM can support richer semantic modeling in applications. This paper introduces the Resource Class Hierarchies into the SLN and investigates to cooperatively model with the RSM. The proposed approach can be used as a normalized semantic overlay of the Knowledge Grid environment. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Mathematical models

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TRANSLATING ONTOLOGIES TO DEFAULT LOGIC

TRANSLATING ONTOLOGIES TO DEFAULT LOGIC

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IFIP TC12 WG12.5-Second IFIP Conference on Artificial Intelligence Applications and Innovations(AIAI2005)

作者： Yu Sun Yuefei Sui Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences Institute of Computer Science and Information Technology Yunnan Normal University

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.

关键词： ontology default logic priority order extension

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A New Pattern Recognition Algorithm Based on Fuzzy Association Degree

A New Pattern Recognition Algorithm Based on Fuzzy Associati...

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International Conference on Neural Networks and Brain (ICNNB)

作者： Shifei Ding Zhongzhi Shi College of Information Science and Engineering Shandong Agricultural University Taian China Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences Institute for Computing Technology Beijing China

Based on fuzzy association degree, a new pattern recognition algorithm is set up. First, some new concepts of fuzzy association coefficient (FAC), fuzzy association degree (FAD) and fuzzy relative weight (FRW) have been proposed for surveying data information. Second, on the basis of the concepts proposed here, a new pattern recognition algorithm has been set up. At last, the algorithm set up here is applied to surveying data. The results of simulation application show that the recognition algorithm presented here is feasible and effective

关键词： Pattern recognition Fuzzy sets Laboratories Fuzzy neural networks Educational institutions information science Agricultural engineering History Artificial neural networks Pattern analysis

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Granular theorem of quotient space in image segmentation

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Jisuanji Xuebao/Chinese Journal of Computers 2005年第10期28卷 1680-1685页

作者： Liu, Ren-Jin Huang, Xian-Wu Department of Computer Science and Technology West Anhui University Lu'an 237012 China Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China School of Electronic and Information Engineering Soochow University Suzhou 215006 China

Based on the quotient space granular theorem, the image segmentation concept is analyzed and the image segmentation methods are studied, and then the quotient space granular theorem of image segmentation is demonstrated. The image segmentation problems are described with triple elements function of the quotient space model (X,f,Γ)⇔([X],[f],[Γ]), according to the quotient space granularity computing, the image segmentation theorem is presented. The methods of images segmentation based on hierarchical and synthesis and combinational technique are exploited and then the segmentation algorithm based granularity synthesis technique is proposed. In this technique, the features of directionality and roughness in texture images data set are firstly extracted respectively to form the different granularities of image, then the different granularity are synthesized according to the theorem of granularity synthesis, finally the texture images is segmented. The experimental results demonstrate that the algorithm is valid for the segmentation of complicated texture images.

关键词： Image segmentation

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Analysis and Applications of PCA information Features

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通讯和计算机（中英文版） 2005年第9期2卷 25-31页

作者： Shifei Ding Zhongzhi Shi College of lnformation Science and Engineering Shandong Agricultural University Tai ＇an 271018 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beo＇ing 100080 China

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A novel feature extraction algorithm

A novel feature extraction algorithm

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Shi-Fei Ding Zhong-Zhi Shi Vun-Cheng Wang Shu-Shan Li College of Information Science and Engineering Shandong Agricultural University Taian China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China

Feature extraction or selection is one of the most important steps in pattern recognition or pattern classification, data mining, machine learning and so on. In this paper, we introduce the information theory, propose a new concept of probability information distance (PID) and prove that the PID satisfies four requests of axiomatization of the distance. So the PID is a kind of distance measure, which can be used to measure the degree of variation between two random variables. We make the PID be separability criterion of the classes for information feature extraction, and call it PID criterion (PIDC). Based on PIDC, we design a novel algorithm for information feature extraction. Compared with principal components analysis (PCA), correlation analysis etc., the algorithm put forward in this paper had regarded for the class information, and so it is a kind of supervised algorithm of feature extraction. The experimental results demonstrate that the algorithm is valid and reliable, and it provides a new research approach for feature extraction, data mining and pattern recognition.

关键词： Feature extraction Pattern recognition Data mining Algorithm design and analysis Principal component analysis Machine learning algorithms Pattern classification Machine learning information theory Random variables

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information feature analysis and improved algorithm of PCA

Information feature analysis and improved algorithm of PCA

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Shi-Fei Ding Zhong-Zhi Shi Yong Liang Feng-Xiang Jin College of Information Science and Engineering Shandong Agricultural University Taian China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China College of Geo-Information Science and Engineering Shandong University of Science and Technology Qingdao China

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 concerned with information function and information entropy of Shannon information theory, consider the inherent characteristic of eigenvalues of matrix, two new concepts of possibility information function (PIF) and possibility information entropy (PIE) are proposed firstly. On the basis of these, the formulae of information rate (IR) and accumulated information rate (AIR) are set up, by which the degree of information compression is measured. In the end, we improve the PCA algorithm called improved principal component analysis (PCA). Through simulated application in practice, the results show that the IPCA proposed here is efficient and satisfactory. It provides a new research approach of information feature compression for pattern recognition.

关键词： information analysis Algorithm design and analysis Principal component analysis information entropy Educational institutions Agricultural engineering Statistical analysis information theory information rates Geographic information Systems

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A logical foundation for ontology representation in NKI

A logical foundation for ontology representation in NKI

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IEEE International Conference on Natural Language processing and Knowledge Engineering (NLP-KE)

作者： Yu Sun Yuefei Sui Institute of Computer Science and Information Technology Yunnan Normal University Kunming China Graduate School Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

A formal representation of ontologies is proposed, based on F-logic and O-logic; and the works in the building of ontologies in NKI. An ontology includes class frames, slot frames, class-slot frames, object frames and axioms. The value restrictions of slots are defined in slot frames. For each slot and each class, there is a class-slot frame representing the specific value restrictions of the slot when defining the class; and the relations between class-slot frames and slot frames are discussed. For a slot in a class frame, its values are inherited to its subclasses without blocking; and its default values are inherited to its subclasses taking overriding, revising and conflict resolution into account. After giving the formal representation of ontologies, the semantics of ontologies are discussed, and main results are presented.

关键词： Ontologies Databases Laboratories intelligent structures information processing Computer science information technology Vocabulary Logic

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Journal of information science and Engineering: Editorial notice

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Journal of information science and Engineering 2005年第5期21卷 i-ii页

作者： Lee, Der-Tsai Amato, Nancy M. Chang, Shih-Fu Chen, Homer H. Chen, Tsuhan Hsu, Tsan-Sheng Hwang, Jenq-Neng Kuo, Sy-Yen Kuo, Tei-Wei Li, Chung-Sheng Tokuyama, Takeshi Wing, Jeannette Wu, Tzong-Chen Yen, John Computer Science at Texas A and M University United States Parasol Laboratory United States IEEE Transactions on Parallel and Distributed Systems Computing Research Association's Committee on the Status of Women in Computing Research CRA-W's Distributed Mentor Program United States Department of Electrical Engineering Columbia University United States Lab. United States College of Electrical Engineering and Computer Science National Taiwan University Taiwan IEEE Transactions on Circuits and Systems for Video Technology IEEE Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States ACM ACM SIGACT IEEE Computer Society IICM Austria Research and Development of the Department Multimedia Signal Processing Technical Committee IEEE Signal Processing Society United States IEEE Transactions on Circuits and systems for Video Technology College of Electrical Engineering and Computer Science National Taiwan Ocean University Keelung Taiwan Department of Electrical Engineering National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan IEEE Technical Committee on Real-Time Systems Computer Science Division IBM T.J. Watson Research Center United States IBM Research Division Graduate School of Information Sciences Tohoku University Japan ACM IPSJ Mathematical Society of Japan Japan Department of Computer Science Computer Science Department Carnegie Mellon University United States National Academies of Science's Computer Science and Telecommunications Board United States Microsoft's Trustworthy Academic Advisory Board Intel Research Pittsburgh's Advisory Board United States Dartmouth's Institute for Security Technology Studies Advisory Committee Canada Sloan Research Fellowships Program Committee United States ACM Taiwan China Information Sciences and Technology Pennsylvania State University United States Laboratory for Intelligent Agents Penn State's School of Info

No abstract available

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A Multi-layers Neural Network Model based on Characteristics of Ganglions' Receptive Fields in Retina and an Algorithm for Watchfulness-keeping

A Multi-layers Neural Network Model based on Characteristics...

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The Third Asian Conference on Vision (ACV2004)

作者：危辉陆汝钤 Department of Computer Science Lab of Algorithm for Cognitive Model Brain Science Research Center Fudan University Shanghai 200433 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing 100080 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing 100080 China

Machine vision is an active branch of Artificial Intelligence. An important problem in this area is the balance among efficiency, accuracy and huge computing. The visual system of human can keep watchfulness to the perimeter of visual field while at same time their central attention is focused to the center of visual field for fine information processing. This mechanism of computing resource assignment could ease the demand for huge and complex hardware structure. Therefore designing computer model based on biological visual

关键词： A Multi-layers Neural Network Model based on Characteristics of Ganglions Receptive Fields in Retina and an Algorithm for Watchfulness-keeping Model

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