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IEEE International Conference on Cognitive Informatics

作者： Peng Zhao Huan-Tong Geng Qing-Sheng Cai University of Science and Technology Hefei China Key Lab. Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei China

After analyzing the disadvantages of traditional text clustering method based on keywords set, a novel approach for clustering of Chinese text based on concept hierarchy is presented. It introduces a Chinese topic classify dictionary as background knowledge to clustering of Chinese text. It adopts a hierarchical coding system which reflects concept relevance among different words and uses vector space model based on concept hierarchy to represent Chinese text. The experimental results show this approach is more effective than traditional text clustering method based on keywords set

关键词： Dictionaries Space technology Clustering methods Documentation Text mining Clustering algorithms Frequency Computer science signal processing signal analysis

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Strong Convergence of Empirical Distribution for a Class of Random Matrices

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Chinese Quarterly Journal of Mathematics 2006年第1期21卷 28-32页

作者： LIANG Qing-wen MIAO Bai-qi WANG Da-peng Department of Statistics and Finance University of Science and Technology of China Hefei 230026 China Key Lab of intelligent Computing and Signal Processing of the Ministry of Education AnhuiUniversity Hefei 230026 China

Let {vij}, i, j = 1, 2, …, be i.i.d, random variables with Ev11 = 0, Ev11^2 = 1 and a1 = （ai1,…, aiM） be random vectors with {aij} being i.i.d, random variables. Define XN =（x1,…, xk） and SN =XNXN^T,where xi=ai×si and si=1/√N（v1i,…, vN,i）^T. The spectral distribution of SN is proven to converge, with probability one, to a nonrandom distribution function under mild conditions.

关键词： empirical spectral distribution function sample covariance matrix Stieltjes transform strong convergence

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Automatic Recognition of Noisy Code-39 Barcode

Automatic Recognition of Noisy Code-39 Barcode

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International Conference on Artificial Reality and Telexistence (ICAT)

作者： Xianyong Fang Fuli Wu Bin Luo Haifeng Zhao Peng Wang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China College of Information Engineering Zhejiang University of Technology China Motorola China Electronics Limited Corporation China

Barcode has been widely applied in the modern world. This paper presents a fast and robust recognition method of noisy code 39 barcode. The proposed method can be divided into two steps: search and decoding. In the first step, all asterisks in the image are found with evenly defined scan lines and then those with the same directions are matched together to get a valid barcode region. In the second step, a local denoise method is first applied to eliminate noise in the barcode region and then a middle band filter is used to decode the barcode. Our method is simple in comparison with former methods and experimental results show that it is efficient for fast barcode recognition on noisy images.

关键词： Decoding Bars Image edge detection Robustness Equations Low pass filters signal processing Educational institutions Educational technology Image recognition

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Granular Analysis of Time Sequence Based on Quotient Space

Granular Analysis of Time Sequence Based on Quotient Space

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International Conference on Computational Intelligence for Modelling, Control and Automation, and International Conference on intelligent Agents, Web Technologies and Internet Commerce

作者： Liquan Zhao Ling Zhang Bo Zhang Province Key Laboratory of Electronic Business Nanjing University of Finance and Economics Nanjing China Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei China Computer Science Department Tsinghua University Beijing China

This paper aims to carry out granular analysis of time sequence based on quotient space. Granular methods have long before been adopted to analyze time sequence, but the granularity was based on time, for example, day mean, month mean, year mean and so on in finance forecast. In this paper, the granularity is based on space and some significant results are obtained: we can, in certain circumstances, get characteristics of time sequence in an original space when carrying out granular analysis of it in its coarser-grain space; granular analysis of a Markov chain is equivalent to an hidden Markov model (HMM), contrarily, any HMM is equivalent to granular analysis of a Markov chain. These results deepened our understanding of HMM from the perspective of granular analysis. We can not only use the methods of HMM to study time sequence, but also use the methods of granular analysis based on quotient space theory to solve the problems of HMM.

关键词： Hidden Markov models Laboratories Artificial intelligence signal analysis Finance signal processing Computer science education Space technology Computational intelligence Economic forecasting

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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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APPROXIMATION MULTIDIMENSION FUCTION WITH FUNCTIONAL NETWORK

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Journal of Electronics(China) 2006年第1期23卷 81-84页

作者： Li Weibin Liu Fang Jiao Licheng Zhang Shuling Li Zongling Institute of Graphics and Image Processing Xianyang Normal University Xianyang 712000 China National Key Laboratory for Radar Signal Processing Xidian University Xi＇an 710071 China Insititute of Intelligent Information Processing Xidian University Xi＇an 710071 China

The functional network was introduced by ***, which extended the neural network. Not only can it solve the problems solved, but also it can formulate the ones that cannot be solved by traditional network. This paper applies functional network to approximate the multidimension function under the ridgelet theory. The method performs more stable and faster than the traditional neural network. The numerical examples demonstrate the performance.

关键词： Functional network Ridgelet Approximation

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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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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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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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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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