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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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Semantic Web Services Composition Using AI Planning of Description Logics

Semantic Web Services Composition Using AI Planning of Descr...

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IEEE Asia-Pacific Conference on Services computing (APSCC)

作者： Lirong Qiu Fen Lin Changlin Wan Zhongzhi Shi Graduate School of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processin Institute of Computing Technology Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

Web services composition techniques are gaining momentum as the opportunity to establish reusable and versatile inter-operability applications. The purpose of semantic Web services is to use semantic specification to automate the discovery, invocation, and composition Web services. Description logics is the formalized foundation of semantic Web services and provides well-defined semantics. And many researchers propose their composition approach based on planning techniques. We propose our service composition methods based on description logics and AI planning technologies. Our algorithm for services composition uses backward-chaining search method to find potential candidate services. And we propose a DAG-based method to generate the planning process and filtering the inappropriate services during the DAG generation process. We test our approach on a simple, yet realistic example, and the preliminary results demonstrate that our implementation provides a practical solution

关键词： Semantic Web Artificial intelligence Logic Web services Ontologies Technology planning Humans Process planning Search methods Filtering

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Rule sets based bilevel decision model 06

Rule sets based bilevel decision model

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Proceedings of the 29th Australasian Computer Science Conference - Volume 48

作者： Z. Zheng G. Zhang Q. He J. Lu Z. Shi Faculty of Information Technology University of Technology Sydney Broadway NSW Australia and Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Faculty of Information Technology University of Technology Sydney Broadway NSW Australia Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781920682309

Bilevel decision addresses the problem in which two levels of decision makers, each tries to optimize their individual objectives under constraints, act and react in an uncooperative, sequential manner. Such a bilevel optimization structure appears naturally in many aspects of planning, management and policy making. However, bilevel decision making may involve many uncertain factors in a real world problem. Therefore it is hard to determine the objective functions and constraints of the leader and the follower when build a bilevel decision model. To deal with this issue, this study explores the use of rule sets to format a bilevel decision problem by establishing a rule sets based model. After develop a method to construct a rule sets based bilevel model of a real-world problem, an example to illustrate the construction process is presented.

关键词： rough set rule set decision model bileval programming decision making

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Completeness of Query Operations on Resource Spaces

Completeness of Query Operations on Resource Spaces

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Hai Zhuge Hai Zhuge Erlin Yao Erlin Yao China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

A great variety of languages can be designed by different people for different purposes to operate resource spaces. Two fundamental issues are: can we design more operations in addition to existing operations? and, how many operations are sufficient or necessary? This paper solves these problems by investigating the theoretical basis for determining how complete a selection capability is provided in a resource operation sublanguage independent of any host language. The result is very useful to the design and analysis of operating languages.

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A computing Model for Concept Fusing and Document Classification

A Computing Model for Concept Fusing and Document Classifica...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Nan Zhang Nan Zhang Chao He Chao He China Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Effective document classification is a long-pursued goal in knowledge management. This paper proposes a novel hybrid approach of semantic representation and statistical measurements. Document is divided into content segments first. By Formal Concept Analysis (FCA), their semantic links with standard concept identifiers are built up whose weights are calculated statistically. In this way, effective concept fusing and document classification can be achieved. In addition, a semantic overlay for specific documents will be constructed via concept fusing. Experiments show our approach is feasible and effective.

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Period information detection from motion capture data

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Journal of Computational information Systems 2006年第2期2卷 551-557页

作者： Li, Zhenbo Deng, Yu Li, Hua Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate School Chinese Academy of Sciences Beijing 100039 China

This paper introduces an approach to detect period information from motion capture data in low dimension. After a motion capture data is obtained, PCA method is utilized for dimension reduction. The accumulation contribution factor is used to determine the analysis dimension. Then the algorithm outputs the period through the low dimension computation. The method is assessed on CMU motion capture database and compared the performance of the automatic methods to that of manually selection. The results show that it has good characteristic for both simple and complex motions. This method can be used for motion database management and motion synthesization.

关键词： information technology

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