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Polarization trend in sponsored search auctions

Polarization trend in sponsored search auctions

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22nd Workshop on Information Technologies and systems, WITS 2012

作者： Yuan, Yong Zeng, Daniel Zhao, Huimin Cheng, Jiesi 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 Sheldon B. Lubar School of Business University of Wisconsin-Milwaukee Milwaukee WI United States

Quality score (QS) plays a critical role in sponsored search auctions and in practice is closely related to the historical click-through rate (CTR) of an advertisement. Existing research, however, has not explicitly considered this correlation between QS and historical CTR. In this paper, we strive to bridge this gap. Based on a discrete time-dependent optimal control model, which explicitly captures the CTR-QS correlation, we analyze the optimal positioning strategy and the widely-observed greedy positioning strategy for advertisers. We find that both strategies lead advertisers to monotonically increase or decrease their ranks over time, and thus may result in a polarization trend in sponsored search markets. Our findings can help characterize advertisers' behavior dynamics and also offer valuable insights and suggestions to search engines.

关键词： Polarization

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A dynamic user adaptive combination strategy for hybrid movie recommendation

A dynamic user adaptive combination strategy for hybrid movi...

引用

IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Cai Chen Daniel Zeng State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

Movie recommendation is a very popular service in internet based movie related websites such as NetFlix, MovieLens. The performance of the recommendation plays the key role in the user experience. Existing works have shown that combining content based and collaborative filtering based algorithms is the best way for movie recommendation. Nevertheless, the performance of this hybrid algorithm is strongly depended on the strategy how to combine the basic pure algorithms. Existing works usually use a static combination strategy which may generate even worse performance for some users. To solve this problems, in this paper we propose a new item based hybrid algorithm that uses a dynamic user adaptive combination strategy. Besides, we also exploit the external open resources IMDB as the movie content data. Experiments on real datasets show that the dynamic user adaptive combination strategy can significantly enhance the performance of the recommendation and the external open resource IMDB is a very good information resource for recommendation.

关键词： Measurement History Algorithm design and analysis DH-HEMTs Filtering algorithms

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A survey of urban traffic coordination controls in intelligent transportation systems

A survey of urban traffic coordination controls in intellige...

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Li, Shuangshuang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan 523808 China

ISBN: (纸本)9781467324007

The urban traffic coordination controls (UTCCs) can make full use of the mutual advantages of intersections, which makes it can improve the traffic access capacity and decrease the possibility of traffic congestion in intersections. This paper gives an overview of UTCCs. After reviewing the concept of UTCCs, we survey the several main hot topics in UTCCs: the correlation degree analysis of intersections, the division approach of traffic control subareas and the objects of coordination. This paper provides a survey of urban traffic coordination controls with the goal of promoting research in this area and concludes with some comments on future research directions. © 2012 IEEE.

关键词： Surveys

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Human action recognition by bagging data dependent representation

Human action recognition by bagging data dependent represent...

引用

International Conference on Pattern Recognition

作者： Wen Zhou Chunheng Wang Baihua Xiao Zhong Zhang Long Ma State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

ISBN: (纸本)9781467322164

Traditional methods based on bag-of-word representation are easily affected by noise, and they also cannot handle the problem when a test distribution differs from the training distribution. In this paper, we propose a novel method for human action recognition by bagging data dependent representation. Different with traditional methods, the proposed method represents each video by several histograms. These histograms are obtained by bagging according to an estimated prior several times in both training and testing. The data dependent property of our method depends on the prior which reflects the training distribution. There are two advantages of the proposed method. First, it alleviates the distribution difference between training set and test set. Second, the bagging operation reduces noise and improves the performance significantly. Experimental results show the effectiveness of the proposed method.

关键词： Data structures Boolean functions Bagging Humans Training Accuracy Noise

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Artificial Transportation System constrution based on ontology-based knowledge base systems

Artificial Transportation System constrution based on ontolo...

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Chen, Songhang Zhu, Fenghua State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songs han Lake Dongguan China

ISBN: (纸本)9781467324007

Artificial Transportation systems (ATS) provide a comprehensive perspective to study actual transportation systems, which are a kind of open and complex giant system referring to diverse engineering and social disciplines. To make use of achievements from related research fields, ontology for ATS is constructed in this paper. Besides conceptual model involved in modeling and applications of ATS, the compatibility with other ontology is considered. Further, an ontological knowledge base with SOA (Service-Oriented Architecture) is designed to manage information and knowledge in ATS. The architecture and interfaces of the knowledge base are presented. Benefit from this, construction and applications of ATS can be conducted on a uniform information and knowledge platform. A case study about traffic jam pattern is demonstrated. © 2012 IEEE.

关键词： Ontology

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Distributed Quadratic Stabilization of Uncertain Linear Multi-Agent systems

Distributed Quadratic Stabilization of Uncertain Linear Mult...

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The 24th Chinese control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

作者： Zhongkui Li Zhisheng Duan Lihua Xie Xiangdong Liu Key laboratory for Intelligent Control &Decision of Complex Systems School of Automation Beijing I State Key Lab for Turbulence and Complex Systems Department of Mechanics and Aerospace Engineering School of Electrical and ElectronicEngineering Nanyang Technological University 639798 Singapore Key laboratory for Intelligent Control & Decision of Complex Systems School of Automation Beijing

This paper considers the distributed quadratic stabilization problems of uncertain continuous-time linear multiagent systems with undirected communication topologies. It is assumed that the agents have identical nominal dynamics while subject to different norm-bounded parameter uncertainties, leading to weakly heterogeneous multi-agent systems. A distributed controller is proposed, based on the relative states of neighboring agents and a subset of absolute states of the agents. It is shown that the distributed quadratic stabilization problem under such a controller is equivalent to the H∞ control problems of a set of decoupled linear systems having the same dimensions as a single agent. A two-step algorithm is presented to construct the distributed robust controller, which does not involve any conservatism and meanwhile decouples the feedback gain design from the communication topology. Furthermore, the distributed quadratic H∞ control problem of uncertain linear multi-agent systems with external disturbances is discussed, which can be reduced to the scaled H∞ control problems of a set of independent systems whose dimensions are equal to that of a single agent.

关键词： Multi-agent system distributed control robustness H∞ control parameter uncertainty

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An embedded co-AdaBoost and its application in classification of software document relation

An embedded co-AdaBoost and its application in classificatio...

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2012 8th International Conference on Semantics, Knowledge and Grids, SKG 2012

作者： Liu, Jin Li, Juan Xie, Yuan Lei, Jeff Hu, Qiping State Key Lab. of Software Engineering Computer School Wuhan University China State Key Lab. of Intelligent Control and Management of Complex Systems Institute of Automation CAS China Department of Computer Science and Engineering University of Texas Arlington TX United States International School of Software Wuhan University China

ISBN: (纸本)9780769547947

To enhance classification performance by making use of easily available unlabelled data to overcome the scarcity of labelled data, this paper proposes an Embedded Co-Adaboost algorithm that integrates multi-view learning into the Adaboost learning framework and at the same time leverages the advantages of Co-training algorithm for performance enhancement. Experimental results demonstrate the effectiveness of the proposed algorithm in terms of the convergence rate, the accuracy, and the steady performance as compared to the original AdaBoost algorithm, without relying on redundant and sufficient feature sets. As a algorithm application in software engineering, the Embedded Co-AdaBoost has been applied to the classification of software document relations to improve the quality of the architecture design documents and the reusability of design knowledge. © 2012 IEEE.

关键词： Reusability

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Research on SVM and FLDA in classification with comparative experiments

Research on SVM and FLDA in classification with comparative ...

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2012 9th IEEE International Conference on Networking, Sensing and control, ICNSC 2012

作者： Qian, Yegan Xiong, Gang Yao, Yanjie Anhui Radio TV Station and Hefei Hanteng Info. Tech. Company Anhui Hefei 230022 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781467303880

The paper discusses two important classification techniques, Fisher's linear discriminated analysis (FLDA) and Support Vector Machine (SVM). First, we propose a theoretical discussion, and then implement FLDA and SVM on several datasets of two classes and multiclass, a comparative experimental analysis among these two techniques aims at exploring and assessing the performance of FLDA and SVM classifiers. To sustain such analysis, the two classification techniques are compared with different training data sets and testing data sets. Different performance indicators have been used to support our experimental studies in a detailed and accurate way such as the classification accuracy. The results obtained on different datasets conclude that FLDA and SVM are valid and effective approaches for pattern classification and conclude their different performance and problems with different size datasets. Meanwhile, the paper employs a non-traditional method to get the training and testing data set, and concludes detailed pros and cons from the experiment results. © 2012 IEEE.

关键词： Support vector machines

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引用

International Joint Conference on Neural Networks (IJCNN)

作者： Shuangyong Song Qiudan Li Xiaolong Zheng State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

The rapid increasing popularity of micro-blogging has made it an important information seeking channel. By detecting recent popular topics from micro-blogging, we have opportunities to gain insights into internet hotspots. Generally, a topic's popularity is determined by two primary factors. One is how frequently a topic is discussed by users, and the other is how much influence those users have, since topics shown in the influential users' posts are more likely to attract others' attention. However, existing approaches interpret a topic's popularity with only the number of keywords related to it, which neglect the importance of the user influence to information diffusion in micro-blogging. In this paper, drawing upon the Cognitive Authority Theory and Social Network Theory, we propose a novel model that detects the most popular topics in micro-blogging with a user interest-based method. The proposed model first constructs a topic graph according to users' interests and their following relationship, and then calculates the topics' popularity with a link-based ranking algorithm. The popular topics detected by the method can reflect the relationship among users' interests, and the topics in the posts of influential users can be highlighted. Experimental results on the data of Twitter, a well-known and feature-rich micro-blogging service, show that the proposed method is effective in popular topic discovery.

关键词： Twitter Blogs Algorithm design and analysis Navigation Vectors Semantics

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Environment coupled metrics learning for unconstrained face verification

Environment coupled metrics learning for unconstrained face ...

引用

IEEE International Conference on Image Processing

作者： Xinyuan. Cai Chunheng. Wang Baihua. Xiao Ji. Zhou Xue. Chen State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Making recognition more reliable under unconstrained environment is one of the most important challenges for realworld face recognition. In this paper, we propose a novel approach for unconstrained face verification. First, we use a spectral-clustering method based on Structural Similarity index to estimate the captured environments of facial images. Then for each pair of environments, we learn two coupled metrics, such that facial images captured in different environments can be transformed into a media subspace, and high recognition performance can be achieved. The coupled transformations are jointly determined by solving an optimization problem in the multi-task learning framework. Experimental results on the benchmark dataset (LFW) show the effectiveness of the proposed method in face verification across varying environments.

关键词： Measurement Face Face recognition Lighting Training Indexes Benchmark testing

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