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Semantic-driven Management and Search for Resources in Research Community

Semantic-driven Management and Search for Resources in Resea...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Junsheng Zhang Junsheng Zhang Zhixian Yan Zhixian Yan Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

In recent years, semantic search has become one hot motivation of the semantic web. In this paper, we propose a semantic-based resource management and search architecture and its implementation in research community, including most of the research relevant resources. We have built two authoring tools respectively for concepts and instances. With the authoring tools, semantic search portal is provided, which has three different interfaces, respectively for retrieval of concept , instance and semantic relationship. Compared with the traditional search methods, semantic search methodology not only gives us more interesting and satisfying search results, whose precision is higher than those of traditional ones only based on keywords, but also displays the results in a more structural and semantic way.

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A Novel Plausible Model for Visual Perception

A Novel Plausible Model for Visual Perception

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Firth IEEE International Conference on cognitive Informatics(第五届认知信息国际会议)

作者： Zhiwei Shi Zhongzhi Shi Hong Hu Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing 200080 China

ISBN: (纸本)1424404754;9781424404759

Traditionally, how to bridge the gap between the low level visual features and the high level semantic concepts has been a tough task for the researchers. In this paper, we propose a novel plausible model, namely globally connected and locally autonomic Bayesian network (GCLABN), to model the process of visual perception. The new model takes advantage of both the low level visual features, such as colors, textures and shapes, of the target object and the interrelationship between the known objects, and integrates them into a Bayesian framework, which possesses both firm theoretical foundation and wide practical applications. According to our meticulous analysis, in many aspects, the novel model theoretically outperforms the original Bayesian network, which has been successfully applied to many related areas, such as object detection, scene analysis and other similar tasks. Finally, although the GCLABN is designed for the visual perception, it also has great potential to be applied to other areas.

关键词： Visualperception Bayesian network.

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3-D Affine Moment Invariants Generated by Geometric Primitives

3-D Affine Moment Invariants Generated by Geometric Primitiv...

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International Conference on Pattern Recognition

作者： Dong Xu Hua Li Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences China

ISBN: (纸本)0769525210

3D affine moment invariants are derived in a convenient way in this paper. The property of volume of a tetrahedron is studied first under affine transformation. 3D affine moment invariants are constructed then by the multiple integrals of the combinations of this kind of geometric primitive. Numerical experiments of deformed models are conducted to certificate the invariance of the new 3D affine moment invariants given in this paper

关键词： Density functional theory Laboratories information processing Computers Deformable models Character recognition Shearing Eigenvalues and eigenfunctions Integral equations Pattern recognition

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3-D Surface Moment Invariants

3-D Surface Moment Invariants

引用

International Conference on Pattern Recognition

作者： Dong Xu Hua Li Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences China

ISBN: (纸本)0769525210

3D surface moments and surface moment invariants under similarity transformation are defined in this paper. This variation of traditional moments and moment invariants can handle the situation where the object is unclosed. 3D surface moment invariants can be used as shape descriptors for the representation of free-form surfaces. Some explicit surface moment invariants are illustrated in the experiment to describe the partial meaningful polygonal patches

关键词： Shape measurement Roentgenium Laboratories information processing Computers Laser modes Application software Character recognition Computational complexity Density functional theory

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Context-aware services composition based on AI planning

Context-aware services composition based on AI planning

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36th Jahrestagung der Gesellschaft fur Informatik e.V. (GI): Informatik fur Menschen, INFORMATIK 2006

作者： Qiu, Lirong Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P. O. Box 2704-28 Beijing 100080 China Graduate School of the Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783885791881

AI planning technologies has proven to be useful for services composition. By treating service as an action, planners do various sorts of reasoning about how to combine services into a plan. However, planners typically support only limited reasoning capabilities which cannot handle the enormous size of the data involved in the planning process over Web. In parallel, the field of context-aware computing has been focusing on providing information that can be used to characterize the situation of an entity, and thereby using context can filter the inappropriate candidate services and adapt to user's preference. The major technical contributions of this paper are: (1) We propose an OWL-SC model for the context-aware composition of Web services. (2) We propose context-aware plan architecture and thus is more scalability and flexibility for the planning process, and thereby improving the efficiency and precision. (3) We propose a hybrid approach to build a plan corresponding to a context-aware service composition, based on global planning and local optimization, considering both the usability and adoption. solution.

关键词： Web services

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On Intelligence Science and Recent Progresses

On Intelligence Science and Recent Progresses

引用

IEEE International Conference on cognitive Informatics

作者： Zhongzhi Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424404759

Summary form only given. Intelligence science is a cross-discipline that dedicates to joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. Brain science explores the essence of brain, research on the principle and model of natural intelligence in molecular, cell and behavior level. cognitive science studies human mental activity, such as perception, learning, memory, thinking, consciousness etc. In order to implement machine intelligence, Artificial intelligence attempts simulation, extension and expansion of human intelligence using artificial methodology and technology. The above three disciplines work together to explore new concept, new theory, new methodology. It will be successful and create a brilliant future in the 21 century. Brain science points out that perceptive lobes have special function separately, the occipital lobe processes the visual information, the temporal lobe processes auditory information, the parietal lobe processes the information from the somatic sensors. All of three lobes deal with information perceived from the physical world. Each lobe is covered with cortex where the bodies of neurons are located. Cortex consists of primary, intermediate and advanced areas at least. information is processed in the primary area first, then is passed to intermediate and advanced areas. Comparing with computer system, the brain is the same as hardware and the mind looks like software. Most work in cognitive science assumes that the mind has mental representations analogous to computer data structures, and computational procedures similar to computational algorithms. Connectionists have proposed novel ideas to use neurons and their connections as inspirations for data structures, and neuron firing and spreading activation as inspirations for algorithms. cognitive science then works with a complex 3-way analogy among the mind, the brain, and computers. Mind, brain, and comp

关键词： Artificial intelligence cognitive science Learning systems Neurons Brain modeling Humans Data structures Computational and artificial intelligence Machine intelligence Temporal lobe

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Logical Connections of Statements in Ontologies

Logical Connections of Statements in Ontologies

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Firth IEEE International Conference on cognitive Informatics(第五届认知信息国际会议)

作者： Cungen Cao Yuefei Sui Yu Sun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080

ISBN: (纸本)9781424404759

In the classical formal logics, the negation can only be applied to formulas. An ontology contains descriptions of individuals, concepts and slots;and statements about individuals, concepts and slots. The negation can be applied to concepts, slots and statements, so that the logical implication should be considered for all possible combinations of individuals, concepts, slots and statements. This paper attempts to give such logical implications between individuals, concepts, slots, statements and their negations.

关键词： Ontologies Concepts Individuals Logical implication Negation.

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Optimization feature compression and FNN realization

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作者： Ding, Shifei Wang, Yuncheng Shi, Zhongzhi Jin, Fengxiang College of Information Science and Engineering Shandong Agricultural University Taian 271018 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China College of Geo-Information Science and Engineering Shandong University of Science and Technology Qingdao 266510 China

ISBN: (纸本)3540372555

Feature compression is one of the most importmant steps in pattern recognition. In this paper, based on minimum squared error (MSE) rule, we first give discrete K-L transform (DKLT). According to idea of entropy function, we propose two new entropy functions-entropy density function (EDF) and representation entropy (RE), by which we can metricize information content of data matrix X. Secondly, an optimization feature compression is put forward and information compression degree is measured by feature compression rate (FCR) and accumulated feature compression rate (AFCR) proposed by authors firstly. In the end, we give an adaptive feedforward neural network (FNN) and improved adaptive FNN to realize optimization feature compression This method can be applied in Biology, Biomathematics, Ecology, and Bioinformation Science and so on for optimization feature compression. keywords: keywords: pattern recognition, optimization feature compression, entropy density function (EDF), representation entropy (RE), feedforward neural network (FNN). © Springer-Verlag Berlin/Heidelberg 2006.

关键词： Feedforward neural networks

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Content-based 3-D Shape Retrieval for Pervasive computing

Content-based 3-D Shape Retrieval for Pervasive Computing

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International Conference on Pervasive computing and Applications (ICPCA)

作者： Dong Xu Hua Li Zongkai Lin Chinese Academy of Sciences China Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Science National Research Center for Intelligent Computing Systems Institute of Computing Technology Chinese Academy of Science. lihua@*** Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences China

3D models are a new kind of cross-media resource which can be frequently seen in the network. Since the amount of them is very huge now, content-based retrieval can help to recognize a certain object or retrieve similar ones from the giant database. This paper presents a new method for deriving 3D moment invariants and uses them as shape descriptors for the representation of 3D models. They are insensitive to surface noise and can be used in pervasive environment conveniently. We also illustrate how to build up experimental system and simulate 3D shape retrieval in wireless environment

关键词： Shape Content based retrieval Pervasive computing information retrieval Humans Internet Application software Laboratories intelligent networks Computer networks

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A Global Geometric Approach for Image Clustering

A Global Geometric Approach for Image Clustering

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International Conference on Pattern Recognition

作者： Sulan Zhang Chunqi Shi Zhiyong Zhang Zhongzhi Shi Chinese Academy of Sciences China Institute of Computing Technology Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences China

ISBN: (纸本)0769525210

We propose an appearance-based image clustering approach called GGCI (global geometric clustering for image). For face images taken with varying pose, expression, eyes (wearing sunglasses or not) or object images under different viewing conditions, GGCI uses easily measured local metric information to learn the underlying global geometry of images space, then apply the extended nearest neighbor approach to cluster images. Different from the usual nearest neighbor approach, GGCI considers the density around the nearest points within clusters. Moreover, our approach clusters based on the geodesic distance measure instead of Euclidean distance measure, which better reflects the intrinsic geometric structure of manifold embedded in high dimensional image space. Experimental results suggest that the proposed GGCI approach achieves lower error rates in image clustering when manifolds are embedded in image space

关键词： Level measurement Nearest neighbor searches Feature extraction Geophysics computing Eyes Euclidean distance Photoreceptors information processing Computers information geometry

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