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International Journal of Digital Content Technology and its Applications 2010年第5期4卷 96-104页

作者： Shifei, Ding Li, Xu Hong, Zhu Liwen, Zhang School of Computer Science and Technology China University of Mining and Technology Xuzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing China

Granular computing (GrC), a knowledge-oriented computing which covers the theory of fuzzy information granularity, rough set theory, the theory of quotient space and interval computing etc, is a way of dealing with incomplete, unreliable, uncertain fuzzy knowledge. In recent years, it is becoming one of the main study streams in Artificial Intelligence (AI). With selecting the size structure flexibly, eliminating the incompatibility between clustering results and priori knowledge, completing the clustering task effectively, cluster analysis based on GrC attracts great interest from domestic and foreign scholars. In this paper, starting from the development of GrC, firstly, the main newly achievements about clustering and GrC are researched and summarized. Secondly, principle of granularity in clustering, the effective clustering algorithms with the idea of granularity as well as their merits and faults are analyzed and evaluated from the point view of rough set, fuzzy sets and quotient space theories. Finally, the feasibility and effectiveness of handling high-dimensional complex massive data with combination of these theories is outlooked.

关键词： Clustering algorithms

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The structural analysis of protein sequences based on the quasi-amino acids code

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Chinese Physics B 2009年第1期18卷 363-369页

作者：朱平唐旭清徐振源 School of Science Jiangnan University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University

Proteomics is the study of proteins and their interactions in a cell. With the successful completion of the Human Cenome Project, it comes the postgenome era when the proteomics technology is emerging. This paper studies protein molecule from the algebraic point of view. The algebraic system （∑, ＋, ＊） is introduced, where ∑ is the set of 64 codons. According to the characteristics of （∑, ＋, ＊）, a novel quasi-amino acids code classification method is introduced and the corresponding algebraic operation table over the set ZU of the 16 kinds of quasi-amino acids is established. The internal relation is revealed about quasi-amino acids. The results show that there exist some very close correlations between the properties of the quasi-amino acids and the codon. All these correlation relationships may play an important part in establishing the logic relationship between codons and the quasi-amino acids during the course of life origination. According to Ma F et al （2003 J. Anhui Agricultural University 30 439）, the corresponding relation and the excellent properties about amino acids code are very difficult to observe. The present paper shows that （ZU, ＋,×） is a field. Furthermore, the operational results display that the eodon tga has different property from other stop codons. In fact, in the mitochondrion from human and ox genomic codon, tga is just tryptophane, is not the stop codon like in other genetic code, it is the case of the Chen W C et al （2002 Acta Biophysiea Siniea 18（1） 87）. The present theory avoids some inexplicable events of the 20 kinds of amino acids code, in other words it solves the problem of ＇the 64 codon assignments of mRNA to amino acids is probably completely wrong＇ proposed by Yang （2006 Progress in Modern Biomedicine 6 3）.

关键词： algebraic operation quasi-amino acids code protein sequences structural analysis

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Automatic video genre categorization and event detection techniques on large-scale sports data 10

Automatic video genre categorization and event detection tec...

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Proceedings of the 2010 Conference of the Center for Advanced Studies on Collaborative Research

作者： Zhang, Ning Duan, Ling-Yu Huang, Qingming Li, Lingfang Gao, Wen Guan, Ling Ryerson Multimedia Research Laboratory Ryerson University Toronto ON Canada Institute of Digital Media Peking University Beijing 100871 China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate University of Chinese Academy of Sciences Beijing 100190 China

This paper presents an efficient and robust automatic process for large-scale sports video analysis. The proposed system firstly identifies the genre of the query video, and then accomplishes the interesting event detection task. The significance of this framework is its automatic characteristic in testing with minimum human involvement in training, as well as the scalability and expansibility in dealing with a large-scale dataset. Domain-knowledge independent local features are extracted from an input video sequence and a histogram based distribution representation is created using the bag-of-visual-words (BoW) model. In genre categorization, k-nearest neighbor (k-NN) classifiers with various dissimilarity measures are assessed and evaluated analytically. For the event detection, a hidden conditional random field (HCRF) structured prediction model is utilized. Overall, this framework demonstrates the efficiency and accuracy in processing voluminous data from sports collection and achieves various tasks in video analysis. It also demonstrates a potential technology transformation from the "laboratory bench" to commercial applications. © 2010 Ning Zhang, Ling-Yu Duan, Qing-ming Huang, Lingfang Li, Wen Gao and Ling Guan.

关键词： Sports

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Shape Recognition and Retrieval Based on Edit Distance and Dynamic Programming

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Tsinghua Science and Technology 2009年第6期14卷 739-745页

作者：潘鸿飞梁栋唐俊王年李薇 Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University

An important aim in pattern recognition is to cluster the given shapes. This paper presents a shape recognition and retrieval algorithm. The algorithm first extracts the skeletal features using the medial axis transform. Then, the features are transformed into a string of symbols with the similarity among those symbols computed based on the edit distance. Finally, the shapes are identified using dynamic programming. Two public datasets are analyzed to demonstrate that the present approach is better than previous approaches.

关键词： skeletal features medial axis transform edit distance dynamic programming

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Distinguishing Patients with Gastritis and Cholecystitis from the Healthy by Analyzing Wrist Radial Arterial Doppler Blood Flow signals

Distinguishing Patients with Gastritis and Cholecystitis fro...

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International Conference on Pattern Recognition

作者： Xiaorui Jiang Dongyu Zhang Kuanquan Wang Wangmeng Zuo Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences China Department of Computer Science and Technology Harbin Institute of Technology China

ISBN: (纸本)9781424475421

This paper tries to fill the gap between Traditional Chinese Pulse Diagnosis (TCPD) and Doppler diagnosis by applying digital signal analysis and pattern classification techniques to wrist radial arterial Doppler blood flow signals. Doppler blood flows signals (DBFS) of patients with cholecystitis, gastritis and healthy people are classified by L2-soft margin SVM and 5 linear classifiers using the proposed feature - piecewise axially integrated bispectra (PAIB). A 5-fold cross validation is used for performance evaluation. The classification accuracies between either two groups of subjects are greater than 93%. Gastritis can be recognized with higher accuracy than cholecystitis. Cholecystitis can be recognized with higher accuracy on left hand data than right. The findings in this paper partly conform to the theory of TCPD. Though the sample size is relatively small, we could still argue that the methods proposed here are effective and could serve as an assistive tool for TCPD.

关键词： Support vector machines Doppler effect Feature extraction Diseases Wrist Pathology Accuracy

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D-LDA: A topic modeling approach without constraint generation for semi-defined classification

HP Laboratories Technical Report

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HP Laboratories Technical Report 2010年第162期

作者： Zhuang, Fuzhen Luo, Ping Shen, Zhiyong He, Qing Xiong, Yuhong Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS China Graduate University Chinese Academy of Sciences China Hewlett Packard Labs China China Innovation Works Australia

We study what we call semi-defined classification, which deals with the categorization tasks where the taxonomy of the data is not well defined in advance. It is motivated by the real-world applications, where the unlabeled data may also come from some other unknown classes besides the known classes for the labeled data. Given the unlabeled data, our goal is to not only identify the instances belonging to the known classes, but also cluster the remaining data into other meaningful groups. It differs from traditional semi-supervised clustering in the sense that in semi-supervised clustering the supervision knowledge is too far from being representative of a target classification, while in semi-defined classification the labeled data may be enough to supervise the learning on the known classes. In this paper we propose the model of Double-latent-layered LDA (D-LDA for short) for this problem. Compared with LDA with only one latent variable y for word topics, D-LDA contains another latent variable z for (known and unknown) document classes. With this double latent layers consisting of y and z and the dependency between them, D-LDA directly injects the class labels into z to supervise the exploiting of word topics in y. Thus, the semi-supervised learning in D-LDA does not need the generation of pairwise constraints, which is required in most of the previous semi-supervised clustering *** present the experimental results on ten different data sets for semi-defined classification. Our results are either comparable to (on one data sets), or significantly better (on the other nine data set) than the six compared methods, including the stateof- the-art semi-supervised clustering methods. © Copyright The Tenth IEEE International Conference on Data Mining, 2010.

关键词： Classification (of information)

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A general approach to extracting full names and abbreviations for Chinese entities from the web

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作者： Jiang, Guang Cungen, Cao Yuefei, Sui Lu, Han Wang, Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences No.6 Kexueyuan South Road Zhongguancun Beijing 100190 China Graduate University of Chinese Academy of Sciences No.19 Yuquan Road Shi Jing Shan Distinct Beijing 100049 China

ISBN: (纸本)3642163262

Identifying Full names/abbreviations for entities is a challenging problem in many applications, e.g. question answering and information retrieval. In this paper, we propose a general extraction method of extracting full names/abbreviations from Chinese Web corpora. For a given entity, we construct forward and backward query items and commit them to a search engine (e.g. Google), and utilize search results to extract full names and abbreviations for the entity. To verify the results, filtering and marking methods are used to sort all the results. Experiments show that our method achieves precision of 84.7% for abbreviations, and 77.0% for full names. © 2010 IFIP.

关键词： Search engines

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Using genetic algorithms to optimize artificial neural networks

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Journal of Convergence Information Technology 2010年第8期5卷 6-6页

作者： Ding, Shifei Xu, Li Su, Chunyang Zhu, Hong School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

Artificial Neural Networks (ANNs), as a nonlinear and adaptive information processing systems, play an important role in machine learning, artificial intelligence, and data mining. But the performance of ANNs is sensitive to the number of neurons, and chieving a better network performance and simplifying the network topology are two competing objectives. While Genetic Algorithms (GAs) is a kind of random search algorithm which simulates the nature selection and evolution, which has the advantages of good global search abilities and learning the approximate optimal solution without the gradient information of the error functions. This paper makes a brief survey on ANNs optimization with GAs. Firstly, the basic principles of ANNs and GAs are introduced, by analyzing the advantages and disadvantages of GAs and ANNs, the superiority of using GAs to optimize ANNs is expressed. Secondly, we make a brief survey on the basic theories and algorithms of optimizing the network weights, optimizing the network architecture and optimizing the learning rules, and make a discussion on the latest research progresses. At last, we make a prospect on the development trend of the theory.

关键词： Genetic algorithms

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On using Tabu Search for RNA secondary structure prediction

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2010年第9期4卷 252-262页

作者： Liu, Yongguo Hao, Jianrui School of Computer Science Engineering University of Electronic Science and Technology of China Chengdu 611731 China Key Laboratory of Intelligent Computing Information Processing of Ministry of Education Xiangtan University Xiangtan 411105 China

In this article, a novel approach is proposed to predict RNA secondary structure called RNA secondary structure prediction based on Tabu Search (RNATS). In the RNATS algorithm, two search models, intensification search and diversification search, are developed to exploit the local regions around the current solution and explore the unvisited solution space, respectively. Simulation experiments are conducted on eight RNA sequences to show that the proposed method is feasible and effective.

关键词： Tabu search

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A novel ant colony genetic hybrid algorithm

Journal of Software

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Journal of Software 2010年第11期5卷 1179-1186页

作者： Gao, Shang Zhang, Zaiyue Cao, Cungen School of Computer Science and Technology Jiangsu University of Science and Technology Zhenjiang 212003 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

By use of the properties of ant colony algorithm and genetic algorithm, a novel ant colony genetic hybrid algorithm, whose framework of hybrid algorithm is genetic algorithm, is proposed to solve the traveling salesman problems. The selection operator is an artificial version of natural selection, and chromosomes with better length of tour have higher probabilities of being selected in the next generation. Based on the properties of pheromone in ant colony algorithm the ant colony crossover operation is given. Four mutation strategies are put forward using the characteristic of traveling salesman problems. The hybrid algorithm with 2-opt local search can effectively find better minimum beyond premature convergence. Ants choose several tours based on trail, and these tours will replace the worse solution. Compare with the simulated annealing algorithm, the standard genetic algorithm and the standard ant colony algorithm, all the 4 hybrid algorithms are proved effective. Especially the hybrid algorithm with strategy D is a simple and effective better algorithm than others. © 2010 ACADEMY PUBLISHER.

关键词： Genetic algorithms

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