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15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013

作者： Ruan, Wenjing Wang, Chaokun Han, Lu Peng, Zhuo Bai, Yiyuan School of Software Tsinghua University Beijing 100084 China Tsinghua National Laboratory for Information Science and Technology Tsinghua University China Department of Computer Science and Technology Tsinghua University China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9783642374005

In some real-world applications, data cannot be measured accurately. Uncertain graphs emerge when this kind of data is modeled by graph data structures. When the graph database is uncertain, our query is highly possibly uncertain too. All of the prior works do not consider the uncertainty of the query. In this paper, we propose a new algorithm called Mutual-Match to solve the problem of uncertain subgraph query under the situation where both the graph dataset and the query are uncertain. Considering that the subgraph isomorphism verification is an NP-hard problem, and it will be more complex on uncertain graph data, the Mutual-Match algorithm uses MapReduce processes to find out all the subgraph matches and can adapt to dynamic graphs well. Experimental results on both real-world and synthetic datasets show the correctness and effectiveness of our proposed methods. © 2013 Springer-Verlag.

关键词： MapReduce

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Embedding with autoencoder regularization

Embedding with autoencoder regularization

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European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2013

作者： Yu, Wenchao Zeng, Guangxiang Luo, Ping Zhuang, Fuzhen He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China University of Science and Technology of China China HP Labs. China China

ISBN: (纸本)9783642409936

The problem of embedding arises in many machine learning applications with the assumption that there may exist a small number of variabilities which can guarantee the "semantics" of the original high-dimensional data. Most of the existing embedding algorithms perform to maintain the locality-preserving property. In this study, inspired by the remarkable success of representation learning and deep learning, we propose a framework of embedding with autoencoder regularization (EAER for short), which incorporates embedding and autoencoding techniques naturally. In this framework, the original data are embedded into the lower dimension, represented by the output of the hidden layer of the autoencoder, thus the resulting data can not only maintain the locality-preserving property but also easily revert to their original forms. This is guaranteed by the joint minimization of the embedding loss and the autoencoder reconstruction error. It is worth mentioning that instead of operating in a batch mode as most of the previous embedding algorithms conduct, the proposed framework actually generates an inductive embedding model and thus supports incremental embedding efficiently. To show the effectiveness of EAER, we adapt this joint learning framework to three canonical embedding algorithms, and apply them to both synthetic and real-world data sets. The experimental results show that the adaption of EAER outperforms its original counterpart. Besides, compared with the existing incremental embedding algorithms, the results demonstrate that EAER performs incremental embedding with more competitive efficiency and effectiveness. © 2013 Springer-Verlag.

关键词： Semantics

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Security games with surveillance cost and optimal timing of attack execution

Security games with surveillance cost and optimal timing of ...

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12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013

作者： An, Bo Brown, Matthew Vorobeychik, Yevgeniy Tambe, Milind Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Southern California Los Angeles CA 90089 United States Sandia National Laboratories Livermore CA 94550 United States

ISBN: (纸本)9781627487665

Stackelberg games have been used in several deployed applications to allocate limited resources for critical infrastructure protection. These resource allocation strategies are randomized to prevent a strategic attacker from using surveillance to learn and exploit patterns in the allocation. Past work has typically assumed that the attacker has perfect knowledge of the defender's randomized strategy or can learn the defender's strategy after conducting a fixed period of surveillance. In consideration of surveillance cost, these assumptions are clearly simplistic since attackers may act with partial knowledge of the defender's strategies and may dynamically decide whether to attack or conduct more surveillance. In this paper, we propose a natural model of limited surveillance in which the attacker dynamically determine a place to stop surveillance in consideration of his updated belief based on observed actions and surveillance cost. We show an upper bound on the maximum number of observations the attacker can make and show that the attacker's optimal stopping problem can be formulated as a finite state space MDP. We give mathematical programs to compute optimal attacker and defender strategies. We compare our approaches with the best known previous solutions and experimental results show that the defender can achieve significant improvement in expected utility by taking the attacker's optimal stopping decision into account, validating the motivation of our work. Copyright © 2013, International Foundation for Autonomous Agents and Multiagent Systems (***). All rights reserved.

关键词： Game theory

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One Sound and Complete <i>R</i>-Calculus with Pseudo-Subtheory Minimal Change Property

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Journal of Computer and Communications 2013年第5期1卷 20-25页

作者： Wei Li Yuefei Sui Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China. State Key Laboratory of Software Development Environment Beijing University of Aeronautics and Astronautics Beijing China

The AGM axiom system is for the belief revision (revision by a single belief), and the DP axiom system is for the iterated revision (revision by a finite sequence of beliefs). Li [1] gave an R-calculus for R-configurations Δ|Γ,?where?Δ?is a set of atomic formulas or the negations of atomic formulas, and?Γ?is a finite set of formulas. In propositional logic programs, one R-calculus N will be given in this paper, such that N is sound and complete with respect to operator s(Δ,t), where s(Δ,t)is a pseudo-theory minimal change of t by?Δ.

关键词： Belief Revision R-Calculus Soundness and Completeness of a Calculus Pseudo-Subtheory

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A new automatic analysis system for risk behaviors

A new automatic analysis system for risk behaviors

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2013 International Conference on Information and Communication Technology for Education (ICTE 2013)

作者： Chan Xu Xin Liu Jian Wu BoYu OuYang Key Laboratory of Intelligent Computing and Information Processing (Xiangtan University) Ministry of Education Institute of Information Engineering Xiangtan University

At present, the software's type forms present diversity, and how to automatically analyze the software's risk behaviors become an urgent problem. This paper used some software behavior crawlers and dynamic analysis method, crawled many representative kinds of malware's behavior, then mapped the behavior as a training data, and combined with BP neural network, established an automated analysis system for risk behaviors. Experiment shows that the system can automatically analyze whether a software is malware, which has better results and a strong practical intelligence.

关键词： risk behavior dynamic analysis malware BP neural network dangerous behaviors intelligence

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Modeling lexical cohesion for document-level machine translation

Modeling lexical cohesion for document-level machine transla...

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23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Xiong, Deyi Ben, Guosheng Zhang, Min Lü, Yajuan Liu, Qun School of Computer Science and Technology Soochow University Suzhou 215006 China Institute for Infocomm Research 1 Fusionopolis Way 21-01 Connexis 138632 Singapore Key Laboratory of Intelligent Information Processing Institute of Computing Technology China Centre for Next Generation Localisation School of Computing Dublin City University Ireland

ISBN: (纸本)9781577356332

Lexical cohesion arises from a chain of lexical items that establish links between sentences in a text. In this paper we propose three different models to capture lexical cohesion for document-level machine translation: (a) a direct reward model where translation hypotheses are rewarded whenever lexical cohesion devices occur in them, (b) a conditional probability model where the appropriateness of using lexical cohesion devices is measured, and (c) a mutual information trigger model where a lexical cohesion relation is considered as a trigger pair and the strength of the association between the trigger and the triggered item is estimated by mutual information. We integrate the three models into hierarchical phrase-based machine translation and evaluate their effectiveness on the NIST Chinese-English translation tasks with large-scale training data. Experiment results show that all three models can achieve substantial improvements over the baseline and that the mutual information trigger model performs better than the others.

关键词： Machine translation

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Exploit spatial relationships among pixels for saliency region detection using topic model

Exploit spatial relationships among pixels for saliency regi...

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19th International Conference on Advances in Multimedia Modeling, MMM 2013

作者： Jiang, Guang Liu, Xi Yue, JinPeng Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100049 China Fujitsu Research and Development Center Co. LTD Beijing 100025 China

ISBN: (纸本)9783642357244

In this paper, we describe an approach to saliency detection as a two-category (salient or not) soft clustering using topic model. In order to simulate human's paralleled visual neural perception, many subregions are sampling from an image, where each one is considered as a set of colors from a codebook, which is a color palette for the image. We assume salient pixels would appear spatial adjacent more possibly, therefore in a same sub-region, while less salient pixels would either. Consequently, all the sub-regions are clustered into two assumed topics with probabilities: "salient"/ "non-salient", while "salient" one is decided to give saliency value of each pixel according to its posterior conditional probability. Our method will give a global saliency map with full resolution, and experiments illustrate it is competitive with the state-of-art methods. © Springer-Verlag 2013.

关键词： Pixels

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A knowledge-based heuristic particle swarm optimization approach with the adjustment strategy for the weighted circle packing problem

A knowledge-based heuristic particle swarm optimization appr...

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作者： Li, Ziqiang Tian, Zhuojun Xie, Yanfang Huang, Rong Tan, Jiyang School of Information and Engineering Xiangtan University Xiangtan Hunan 411105 China Key Laboratory of Intelligent Computing and Information Processing Xiangtan University Ministry of Education Xiangtan Hunan 411105 China School of Mathematics and Computer Science Xiangtan University Xiangtan Hunan 411105 China

The weighted circle packing problem is a kind of important combination optimization problem and has the NP-hard property. Inspired by the No Free Lunch Theorem, a knowledge-based heuristic particle swarm optimization approach with the adjustment strategy (KHPSOA) is developed for this problem. The knowledge (e.g., the relation between its weight matrix and better solution) is obtained from this problem itself and existing layout scheme diagrams and applied to form more effective ordering and positioning rules of the proposed heuristic method. A better layout scheme of larger circles is obtained through the heuristic method. The optimal solution of this problem is obtained by inserting a few residual smaller circles into the gaps of the better layout scheme and further optimizing it through the proposed particle swarm optimization with the adjustment strategy. The numerical experiments show that KHPSOA is superior to the existing algorithms in the performances. © 2013 Elsevier Ltd. All rights reserved.

关键词： Heuristic methods

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One Sound and Complete R-Calculus with Pseudo-Subtheory Minimal Change Property

One Sound and Complete R-Calculus with Pseudo-Subtheory Mini...

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2013 Conference on Artificial Intelligence and Data Mining(AIDM 2013);2013 Business Economics and Investment Conference(BEI 2013);2013 Water Pollution and Treatment Conference(WPT 2013)

作者： Wei Li Yuefei Sui State Key Laboratory of Software Development Environment Beijing University of Aeronautics and Astronautics Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences

The AGM axiom system is for the belief revision (revision by a single belief),and the DP axiom system is for the iterated revision (revision by a finite sequence of beliefs).Li [1] gave an R-calculus for R-configurations Δ| Γ,where Δ is a set of atomic formulas or the negations of atomic formulas,and Γ is a finite set of *** propositional logic programs,one R-calculus N will be given in this paper,such that N is sound and complete with respect to operator s (Δ,t),where s (Δ,t)is a pseudo-theory minimal change of t by Δ .

关键词：

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The Sound and Complete R-Calculi with Respect to the Set-Based and Inference-Based Minimal Change

The Sound and Complete R-Calculi with Respect to the Set-Bas...

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2013 Asia-Pacific Computational Intelligence and Information Technology Conference(APCIIT 2013)

作者： LI WEI YUEFEI SUI State Key Laboratory of Software Development Environment Beijing University of Aeronautics and Astronautics Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences

The AGM axiom system is for the belief revision(revision by a single belief), and the DP axiom system is for the iterated revision(revision by a finite sequence of beliefs). Li[1] gave an R-calculus for R-configurations |Γ, where is a set of atomic formulas or the negations of atomic formulas, and Γ is a finite set of formulas. The set-based minimal change and inference-based minimal change are distinguished in this paper, and two R- calculi V and N are given so that V and N are sound and complete with respect to the set-based minimal change and the inference-based minimal change, respectively.

关键词： Belief Revision,R-Calculus,Minimal Change,Contraction,Soundness and Completeness.

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