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Co-evolution-based mechanism design for sponsored search advertising

ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS 2012年第6期11卷 537-547页

作者： Yuan, Yong Zeng, Daniel Univ Arizona Dept Management Informat Syst Tucson AZ 85721 USA Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing Peoples R China Beijing Engn Res Ctr Intelligent Syst & Technol Beijing Peoples R China

Sponsored search advertising (SSA), the primary revenue source of Web search engine companies, has become the dominant form of online advertising. Search engine companies, such as Google and Baidu, are naturally interested in SSA mechanism design with the aim to improve the overall effectiveness and profitability of SSA ecosystems. Due to model intractability, however, traditional game theory and mechanism design frameworks provide only limited help as to the design and evaluation of practical SSA mechanisms. In this paper, we propose a niche-based co-evolutionary simulation approach, aiming at computationally evaluating SSA auction mechanisms based on advertisers' equilibrium bidding behavior generated through co-evolution of their bidding strategies. Using this approach, we evaluate and compare key performance measures of several practical SSA auction mechanisms, including the generalized first and second price auction, the Vickrey-Clarke-Groves mechanism, and a novel hybrid mechanism adopted by ***, a major search engine in China. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Sponsored search advertising Mechanism design Co-evolutionary simulation Niche-based evolution

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Extracting opinion explanations from Chinese online reviews

Extracting opinion explanations from Chinese online reviews

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2012 10th IEEE International Conference on Intelligence and Security Informatics, ISI 2012

作者： Li, Yuequn Mao, Wenji Zeng, Daniel Huangfu, Luwen Liu, Chunyang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Management Information Systems University of Arizona Tucson AZ United States CNCERT/CC Beijing China

ISBN: (纸本)9781467321037

Opinion mining has gained increasing attention and shown great practical value in recent years. Existing research on opinion mining mainly focuses on the extraction of lexicon orientation and opinion targets. The explanations of opinions, which are potentially valuable for many applications, are totally ignored. To address this specific research challenge, in this paper, we propose an approach to extract the explanation of reason and/or consequence behind an opinion via learning word pairs and using causal indicators from Chinese online reviews. We also improve our word pair based method by constructing clusters of word paris. Experiments on a Chinese business review corpus show that our method is feasible and effective. © 2012 IEEE.

关键词： Sentiment analysis

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Acquiring netizen group's opinions for modeling food safety events

Acquiring netizen group's opinions for modeling food safety ...

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2012 10th IEEE International Conference on Intelligence and Security Informatics, ISI 2012

作者： Tan, Zhangwen Mao, Wenji Zeng, Daniel Li, Xiaochen Bao, Xiuguo State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Management Information Systems University of Arizona Tucson AZ United States CNCERT/CC Beijing China

ISBN: (纸本)9781467321037

Food safety events are typical public security events that draw great public concern. In food safety events, millions of netizens pay close attention to the event, express their opinions online and thus influence the decisions of government or food producers. Modeling netizen groups, especially the dynamics of their opinions in these events, can help us understand the mechanism and evolvement of such events and provide valuable insights for social management. However, conventional computational models, such as agent-based models, are usually constructed manually. In this paper, we propose an approach to acquiring netizen group's opinions from online comments to facilitate the modeling of food safety events. We conduct experimental study on typical events happened in China and empirically evaluate the performance of our proposed approach. The results verify the effectiveness of the approach. © 2012 IEEE.

关键词： Computational methods

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Gabor face recognition by multi-channel classifier fusion of supervised kernel manifold learning

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NEUROCOMPUTING 2012年 97卷 398-404页

作者： Zhao, Zeng-Shun Zhang, Li Zhao, Meng Hou, Zeng-Guang Zhang, Chang-Shui Shandong Univ Sci & Technol Shandong Prov Key Lab Robot & Intelligent Technol Coll Informat & Elect Engn Qingdao 266590 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Tsinghua Univ Dept Automat Tsinghua Natl Lab Informat Sci & Technol State Key Lab Intelligent Technol & Syst Beijing 100084 Peoples R China

Motivated by the multi-channel nature of the Gabor feature representation and the success of the multiple classifier fusion, and meanwhile, to avoid careful selection of parameters for the manifold learning, we propose a face recognition framework under the multi-channel fusion strategy. The Gabor wavelet endows the algorithm in a similar way as the human visual system, to represent face features. To solve the curse of dimensionality due to multi-channel Gabor feature, as well as to preserve nonlinear labeled intrinsic structure of the sample points, the manifold learning is applied to model the nonlinear labeled intrinsic structure. Each of the filtered multi-channel Gabor features, is treated as an independent channel. Classification is performed in each channel by the component classifier and the final result is obtained using the decision fusion strategy. The experiments on three face datasets show effective and encouraging recognition accuracy compared with other existing methods. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Face recognition Supervised kernel manifold learning Classifier fusion Gabor wavelet

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A New Calibration Method for an Inertial and Visual Sensing System

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International Journal of Automation and computing 2012年第3期9卷 299-305页

作者： Xu, De Wang, Hua-Wei Li, You-Fu Tan, Min State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China East China Research Institute of Electronic Engineering Hefei 230088 China Department of Manufacturing Engineering and Engineering Management City University of Hong Kong Hong Kong China

The relative pose between inertial and visual sensors equipped in autonomous robots is calibrated in two steps. In the first step, the sensing system is moved along a line, the orientations in the relative pose are computed from at least five corresponding points in the two images captured before and after the movement. In the second step, the translation parameters in the relative pose are obtained with at least two corresponding points in the two images captured before and after one step motion. Experiments are conducted to verify the effectiveness of the proposed method.

关键词： Inertial sensor visual sensor calibration motion estimation robot vision.

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Data-Wave-Based Features Extraction and Its Application in Symbol Identifier Recognition and Positioning Suitable for Multi-Robot systems Regular Paper

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INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC systems 2012年第6期9卷

作者： Liu, Xilong Qian, Hanbo Cao, Zhiqiang Zhou, Chao Yang, Yuequan Tan, Min Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China SASTIND Ctr Coordinat & Support Beijing Peoples R China Yangzhou Univ Coll Informat Engn Yangzhou Peoples R China

In this paper, feature extraction based on data-wave is proposed. The concept of data-wave is introduced to describe the rising and falling trends of the data over the long-term which are detected based on ripple and wave filters. Supported by data-wave, a novel symbol identifier with significant structure features is designed and these features are extracted by constructing pixel chains. On this basis, the corresponding recognition and positioning approach is presented. The effectiveness of the proposed approach is verified by experiments.

关键词： Data-wave Symbol identifier Structure features Pixel chain Recognition and positioning

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Measuring Driving Behaviors from Live Video

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IEEE INTELLIGENT systems 2012年第5期27卷 75-80页

作者： Wang, Kunfeng Huang, Wuling Tian, Bin Wen, Ding Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100864 Peoples R China Natl Univ Def Technol Ctr Mil Computat Expt & Parallel Syst Technol Changsha Hunan Peoples R China

Because of the technical and cost constraints on traditional measurement methods, there is a lack of long-term driving behavior data from natural traffic scenes, and this situation has been hindering research progress into driving behavior modeling and other related topics. Thanks to high-definition cameras and advanced visual measurement methods, traffic visual detection is entering a new stage of traffic visual measurement, and thus we can expect to achieve accurate segmentation, positioning, and measurement for road vehicles from live video to meet the requirement for field test data in behavior modeling. To measure driving behaviors in a cost-effective manner, the authors propose a comprehensive visual measurement approach that could perform well in complex traffic scenes. Specifically, they describe a procedure for traffic visual measurement, some preliminary algorithms, and some representative experimental results. Comparisons between the proposed method and three traditional ones (driving simulator, in-vehicle data recorder, and remote-sensing camera) indicate that the biggest advantage of the proposed method is it can measure driving behaviors from live video. Hence, the ongoing research will greatly benefit cognition in driving behavior models.

关键词： Cameras Image Segmentation Measurement Object Detection Road Traffic Traffic Engineering Computing Video Signal Processing Driving Behavior Measurement Live Video Technical Constraints Cost Constraints Long Term Driving Behavior Data Natural Traffic Scenes Driving Behavior Modeling Advanced Visual Measurement Methods Traffic Visual Detection Traffic Visual Measurement Road Vehicle Segmentation Road Vehicle Positioning Road Vehicle Measurement Comprehensive Visual Measurement Approach Driving Simulator In Vehicle Data Recorder Remote Sensing Camera Intelligent Transportation systems Intelligent Vehicles Costs Road Vehicles Visualization Data Models Cameras Remote Sensing Cognition Computer Vision Traffic Visual Measurement Driving Behaviors Vehicle Segmentation Live Video

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A symbol identifier based recognition and relative positioning approach suitable for multi-robot systems 1

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5th International Conference on Intelligent Robotics and Applications, ICIRA 2012

作者： Qian, Hanbo Yuan, Wenbo Liu, Xilong Cao, Zhiqiang Zhou, Chao Tan, Min Center of Coordination and Support of SASTIND Beijing 100081 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (数字)9783642335037

ISBN: (纸本)9783642335020

In this paper, a symbol identifier based recognition and relative positioning approach suitable for multi-robot systems is proposed. The symbol identifier is composed of central area and peripheral area, and there exists radial spokes in central area. The recognition approach utilizes some features including luminance feature of center point, luminance difference between center point and its ambient region, the number and distribution of spokes as well as the shape of peripheral area to filter the points in the image. Finally, the resulting pixel points set to characterize the center points of symbol identifiers is generated. On this basis, the positions of these center points relative to the camera are then calculated. The proposed approach is verified by the experiments. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Multipurpose robots

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A novel pipeline for motif discovery, pruning and validation in promoter sequences of human tissue specific genes

A novel pipeline for motif discovery, pruning and validation...

引用

2012 IEEE 6th International Conference on systems Biology, ISB 2012

作者： Gong, Xiu-Jun Yu, Hua Zhao, Fei-Fei School of Computer Science and Technology Tianjin University Tianjin China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Science Beijing China

ISBN: (纸本)9781467343985

Identification and analysis of tissue-specific (TS) genes and their regulatory activities play an important role in the understanding of mechanisms of organisms, disease diagnosis and drug design. In this paper, we designed a pipeline for the discovery of promoter motifs for tissue-specific genes. The pipeline consists of three phases: motif searching, motif merging and motif validation. The motif searching phase integrated three algorithms: MEME, AlignACE and Gibbs Sampling. In the second phase, we proposed a motif merging method, which is based on Bayesian probabilistic principles, to reduce redundancies of motifs from the first phase. Lastly, the motif validation phase verified the statistical significance of discovered motifs using a Bayesian Hypothesis Test approach. We performed the analysis on the sequences of promoter regions (-449bp-1000bp) of 4,552 human tissue-specific genes across 82 tissues and 924 housekeeping genes. The distributions of motifs in different promoter regions show that most motifs prefer to be in the proximal region (+500∼50bp, -50bp∼-500bp) of promoters. © 2012 IEEE.

关键词： Pipelines

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Multimodal swimming control of a robotic fish with pectoral fins using a CPG network

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Chinese Science Bulletin 2012年第10期57卷 1209-1216页

作者： WANG Ming YU JunZhi TAN Min ZHANG JianWei School oflnformation and Electrical Engineering Shandong Jianzhu University Jinan 250101 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department oflnformatics University of Hamburg Hamburg D-22527 Germany

The neural-based approaches inspired by biological neural mechanisms of locomotion are becoming increasingly popular in robot *** paper investigates a systematic method to formulate a Central Pattern Generator(CPG) based control model for mul-timodal swimming of a multi-articulated robotic fish with flexible pectoral fins.A CPG network is created to yield diverse swim-ming in three dimensions by coupling a set of nonlinear neural oscillators using nearest-neighbor *** particular,a sensitivity analysis of characteristic parameters and a stability proof of the CPG network are *** the coordinated con-trol of the joint CPG,caudal fin CPG,and pectoral fin CPG,a diversity of swimming modes are defined and successfully *** latest results obtained demonstrate the effectiveness of the proposed *** is also confirmed that the CPG-based swimming control exhibits better dynamic invariability in preserving rhythm than the conventional body wave method.

关键词：网络控制多式联运机器鱼中央游泳胸鳍人民政府神经机制

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