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2011 International Conference on Computer Science and Service System, CSSS 2011

作者： Zhang, Zeliang Li, Xiongfei Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China Beihua University Jilin China

ISBN: (纸本)9781424497638

Visual voice lip-reading, so the computer can understand what the speakers want to express direction by looking at their lips. Lip reading is the easiest way to compare the early characters and templates from the frozen image is stored. It ignores the very nature and time changes. This method is very simple, but it's just simple elements can be classified, then it may not show significant speech recognition services. Behavior was characterized by more and more common. Because of the hidden Markov model is superior (HMM), which can be widely used in speech recognition. In recent years, is also used to lip reading identification. Classical HMM model, so that the two assumptions: hidden assumptions collected: in t+1 the state can only be in this country is not in the state before t;from the hidden visible state hypothesis: only by regulating the t hide the visible state, rather than the previous state. This hypothesis is not very useful in some applications (such as lip reading) is reasonable. Under certain conditions, in the t state not only limits the t1, but also t2. Therefore, this study modified the assumptions of the classical HMM to derive a new HMM model and algorithms, and applied to the lip-reading recognition is increasing discrimination. © 2011 IEEE.

关键词： Hidden Markov models

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Communities detection with applications to real-world networks analysis

Communities detection with applications to real-world networ...

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2011 7th International Conference on computational Intelligence and Security, CIS 2011

作者： Yang, Bo School of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9780769545844

Community structure is one of non-trivial topological properties ubiquitously demonstrated in real-world complex networks. Related theories and approaches are of fundamental importance for understanding the functions of networks. Previously, we have proposed a probabilistic algorithm called the NCMA to efficiently as well as effectively mine communities from real-world networks. Here, we show that the NCMA can be readily extended and applied to address a wide range of network oriented applications beyond community detection including ranking, characterizing and searching real-world networks. © 2011 IEEE.

关键词： Complex networks

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A new feature selection method based on clustering

A new feature selection method based on clustering

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2011 8th International Conference on Fuzzy Systems and knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural computation, ICNC'11

作者： Liu, Huawen Mo, Yuchang Wang, Jiyi Zhao, Jianmin Department of Computer Science Zhejiang Normal University Jinhua 321004 China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun 130012 China School of Computer Science and Engineering Southeast University Nanjing 211189 China

ISBN: (纸本)9781612841816

Feature selection is an effective technique to put the high dimension of data down, which is prevailing in many application domains, such as text categorization and bio-informatics, and can bring many advantages, such as improving efficiency and avoiding over-fitting, to learning algorithms. Currently, many efforts have been attempted in this field and various feature selection methods have been developed and proved to be very competitive. Unlike other selection methods, in this paper we propose a new method to select important features using a manner of feature clustering. The main character of our method is that it works like data clustering in an agglomerative way. In this method, each feature is considered as a data point clustered with between-cluster and within-cluster distances. As a result, the selected feature subset has minimal redundancy among its members and maximal relevance with the class labels. Our performance evaluations on seven benchmark datasets show that the classification performance achieved by our proposed method is better than other feature selection methods. © 2011 IEEE.

关键词： Feature Selection

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A novel method for RNA secondary structure prediction

A novel method for RNA secondary structure prediction

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2011 7th International Conference on Natural computation, ICNC 2011

作者： Xing, Chong Ji, Zhaohua Wang, Gang Wang, Yao Shen, Wei Liang, Yanchun Key Laboratory for Symbol Computation and Knowledge Engineering of National Education MinistryCollege of Computer Science and TechnologyJilin University Changchun China College of Information Engineering Guanghua College of Changchun University Changchun China College of Communications Engineering Jilin University Changchun China

ISBN: (纸本)9781424499533

In this paper, we propose PSOfold, a particle swarm optimization for RNA secondary structure prediction. PSOfold is based on the recently published IPSO. We present two strategies to improve the performance of IPSO. Firstly, in order to boost the competence in searching an optimal solution, fuzzy logic control is used to adaptively adjust the parameters in PSO. Accordingly, three fuzzy logic controls are designed by which the inertia weight, learning factors and the number of ants are tuned respectively. Secondly, to further settle the stem permutation problem, we put forward a solution conversion strategy (SCS), which can transform discrete values of stems into an ordered stem combination, thereby supplying an enhanced solution to evaluation of objective function. An evaluation of the performance of PSOfold in terms of prediction accuracy is made via comparison with one dynamic programming algorithm mfold and four metaheuristics, IPSO, ACRNA, RnaPredict, SARNA-Predict and mfold for ten individual known structures. PSOfold is able to predict structures with higher prediction accuracy than the other metaheuristic based methods on certain sequences, and has comparable performance compared with mfold. © 2011 IEEE.

关键词： Particle swarm optimization (PSO)

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A Chinese online document clustering algorithm based on hidden sentiment vector

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Journal of computational Information Systems 2011年第6期7卷 1974-1981页

作者： Yang, Hui Wang, Zhe Zhou, Xu Wang, Zuo Zhou, Tong College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory for Symbol Computation and Knowledge Engineering Ministry of Education China

The core idea of clustering algorithm is the division of data into groups of similar objects. Some clustering algorithms are proven good performance on document clustering, such as k-means and UPGMA etc. However, few document clustering algorithms pay attention to the hidden sentiment which is a very important feature of the documents. This paper presents an improved k-means algorithm (HSK-Means) based on hidden sentiment vector for Chinese document clustering. Chinese dependency grammar rules are used to extract document feature and evaluate hidden sentiment. A new method for selecting initial cluster centroids based on rank mechanism of similarity is also proposed to improve accuracy of clustering algorithm. The experimental results on real online document sets illustrate that the performance of HSK-Means algorithm is better than classic document clustering algorithms. Copyright © 2011 Binary Information Press.

关键词： Information retrieval

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A kind of improving HMM model and using in the visual speech recognition

A kind of improving HMM model and using in the visual speech...

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2011 International Conference on Computer Science and Service System, CSSS 2011

作者： Zhang, Zeliang Li, Xiongfei Yang, Chengjia Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China Beihua University Jilin China

ISBN: (纸本)9781424497638

Visual speech-lip reading, making the computer understands what do speakers want to express through observing the lip direction of them. The most simply method of lip reading in early stage is to compare between characters from the frozen pictures and templates being stored. It neglects the character is changing with time. This method is very simply, but it only can classify the simple elements not the words, so it couldn't render great serves to speech recognition. Afterwards the adoption of behavioral characteristics is becoming more widespread. Because of the superior of Hidden Markov model (HMM), it can be applied in speech recognition widely. In recent years, it is also used in the research of lip-reading recognition. The classical HMM model makes two hypotheses: hidden expropriation hypothesis: the state at t+1 is only conditioned by the state at t, not the state before;the expropriation hypothesis from hidden state to visible state: the visible state at t only conditioned by the hidden state at t, not the state before. Such kind of hypothesis is not very reasonable in some practical application (such as lip-reading). In some kind condition, the state at t is not only conditioned by t-1, but also t-2. Therefore this thesis revises the assumed condition classical HMM to derive a new HMM model and algorithm, and applying it into lip-reading recognition to increase the discrimination. © 2011 IEEE.

关键词： Hidden Markov models

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Communities Detection with Applications to Real-World Networks Analysis

Communities Detection with Applications to Real-World Networ...

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International Conference on computational Intelligence and Security

作者： Bo Yang School of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China

关键词： Communities Probability distribution Dolphins Social network services Probabilistic logic Prediction algorithms Clustering algorithms

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An Approach for Calculating Semantic Similarity between Words Using WordNet

An Approach for Calculating Semantic Similarity between Word...

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International Conference on Digital Manufacturing and Automation (ICDMA)

作者： Dou Hao Wanli Zuo Tao Peng Fengling He College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China

This paper presents a new edge-counting based method using Word Net to compute the similarity. The method achieves a similarity that perfectly fits with human rating and effectively simulate the human tHought process that is people prefer to consider more differences when the semantic distance between two word is closer, and vice versa. At last, we weigh up our model against a benchmark set by human similarity judgment, and obtain a much improved result compared with other methods.

关键词： Semantics Humans computational modeling Correlation Educational institutions Benchmark testing Smoothing methods

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A kind of improving HMM model and using in the visual speech recognition

A kind of improving HMM model and using in the visual speech...

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International Conference on Computer Science and Service System (CSSS)

作者： Zeliang Zhang Xiongfei Li Chengjia Yang Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Beihang University Jilin China

Visual speech-lip reading, making the computer understands what do speakers want to express through observing the lip direction of them. The most simply method of lip reading in early stage is to compare between characters from the frozen pictures and templates being stored. It neglects the character is changing with time. This method is very simply, but it only can classify the simple elements not the words, so it couldn't render great serves to speech recognition. Afterwards the adoption of behavioral characteristics is becoming more widespread. Because of the superior of Hidden Markov model (HMM), it can be applied in speech recognition widely. In recent years, it is also used in the research of lip-reading recognition. The classical HMM model makes two hypotheses: hidden expropriation hypothesis: the state at t+1 is only conditioned by the state at t, not the state before; the expropriation hypothesis from hidden state to visible state: the visible state at t only conditioned by the hidden state at t, not the state before. Such kind of hypothesis is not very reasonable in some practical application (such as lip-reading). In some kind condition, the state at t is not only conditioned by t-1, but also t-2. Therefore this thesis revises the assumed condition classical HMM to derive a new HMM model and algorithm, and applying it into lip-reading recognition to increase the discrimination.

关键词： Hidden Markov models Viterbi algorithm Speech recognition knowledge engineering Laboratories Electronic mail Medical services

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A study on improved hidden Markov models and applications to speech recognition

A study on improved hidden Markov models and applications to...

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International Conference on Computer Science and Service System (CSSS)

作者： Zeliang Zhang Xiongfei Li Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Beihang University Jilin China

Visual voice lip-reading, so the computer can understand what the speakers want to express direction by looking at their lips. Lip reading is the easiest way to compare the early characters and templates from the frozen image is stored. It ignores the very nature and time changes. This method is very simple, but it's just simple elements can be classified, then it may not show significant speech recognition services. Behavior was characterized by more and more common. Because of the hidden Markov model is superior (HMM), which can be widely used in speech recognition. In recent years, is also used to lip reading identification. Classical HMM model, so that the two assumptions: hidden assumptions collected: in t+1 the state can only be in this country is not in the state before t; from the hidden visible state hypothesis: only by regulating the t hide the visible state, rather than the previous state. This hypothesis is not very useful in some applications (such as lip reading) is reasonable. Under certain conditions, in the t state not only limits the t-1, but also t-2. Therefore, this study modified the assumptions of the classical HMM to derive a new HMM model and algorithms, and applied to the lip-reading recognition is increasing discrimination.

关键词： Hidden Markov models Mouth Speech recognition Cost accounting Training Viterbi algorithm Algorithm design and analysis

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