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2010-06-04
Bayesian Network Technologies: Applications and Graphical Models (Hardcover)
Ankush Mittal (Author), Ankush Mittal; Ashraf Kassim (Editor)

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Product Description
Bayesian networks are now being used in a variety of artificial intelligence applications. These networks are high-level representations of probability distributions over a set of variables that are used for building a model of the problem domain. Bayesian Network Technologies: Applications and Graphical Models provides an excellent and well-balanced collection of areas where Bayesian networks have been successfully applied. This book describes the underlying concepts of Bayesian Networks in an interesting manner with the help of diverse applications, and theories that prove Bayesian networks valid. Bayesian Network Technologies: Applications and Graphical Models provides specific examples of how Bayesian networks are powerful machine learning tools critical in solving real-life problems.


Product Details
  • Hardcover: 300 pages
  • Publisher: IGI Publishing (March 30, 2007)
  • Language: English
  • ISBN-10: 1599041413
  • ISBN-13: 978-1599041414
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2010-6-4 07:27:54

Table of Contents


Forewordvi


Prefacevii


Section I:


Modeling and Classification Using Bayesian Networks


Chapter I


A Novel Discriminative Naive Bayesian Network for Classification 1


Kaizhu Huang, Fujitsu Research and Development Centre Co Ltd, China
Zenglin Xu, Chinese University of Hong Kong Shatin, Hong Kong
Irwin King, Chinese University of Hong Kong Shatin, Hong Kong
Michael R Lyu, Chinese University of Hong Kong Shatin, Hong Kong
Zhangbing Zhou, Bell-Labs, Lucent Technologies, China

Chapter II


A Bayesian Belief Network Approach for Modeling Complex Domains 13


Ben K Daniel, University of Saskatchewan, Canada
Juan-Diego Zapata-Rivera, Educational Testing Service, USA
Gordon I McCalla, University of Saskatchewan, Canada

Chapter III


Data Mining of Bayesian Network Structure Using a Semantic Genetic Algorithm-Based Approach 42


Sachin Shetty, Old Dominion University, USA


Min Song, Old Dominion University, USA


Mansoor Alam, University of Toledo, USA


Chapter IV


NetCube: Fast, Approximate Database Queries Using Bayesian Networks 54


Dimitris Margaritis, Iowa State University, USA


Christos Faloutsos, Carnegie Mellon University, USA


Sebastian Thrun, Stanford University, USA


Chapter V


Applications of Bayesian Networks in Reliability Analysis 84


Helge Langseth, Norwegian University of Science and Technology, Norway


Luigi Portinale, University of Eastern Piedmont, Italy


Chapter VI


Application of Bayesian Modeling to Management Information Systems: A Latent Scores Approach 103


Sumeet Gupta, National University of Singapore, Singapore


Hee-Wong Kim, National University of Singapore, Singapore


Section II:


Bayesian network for Image Processing and Related Applications


Chapter VII


Bayesian Networks for Image Understanding 128


Andreas Savakis, Rochester Institute of Technology, USA


Jiebo Luo, Eastman Kodak Research Laboratories, USA


Michael Kane, Yale University, USA


Chapter VIII


Long Term Tracking of Pedestrians with Groups and Occlusions 151


Pedro M Jorge, Polytechnic Institute of Lisbon, Portugal


Arnaldo J Abrantes, Polytechnic Institute of Lisbon, Portugal


João M Lemos, INESC-ID/Instituto Superior Técnico, Portugal


Jorge S Marques, Instituto de Sistemas e Róbotica and Instituto Superior


Técnico, Lisbon, Portugal


Chapter IX


DBN Models for Visual Tracking and Prediction 176


Qian Diao, Intel China Research Center, China


Jianye Lu, Intel China Research Center, China


Wei Hu, Intel China Research Center, China


Yimin Zhang, Intel China Research Center, China


Gary Bradski, Microprocessor Research Lab/Intel Research, USA

Chapter X


Multimodal Human Localization Using Bayesian Network Sensor Fusion 194


David Lo, Carleton University, Canada


Chapter XI


Retrieval of Bio-Geophysical Parameters from Remotely Sensing Data by Using Bayesian Methodology 222


C Notarnicola, University of Bari, Italy

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2010-6-4 07:28:26

Section III:


Bayesian networks for Bioinformatics Applications


Chapter XII


Application of Bayesian Network in Drug Discovery and Development


Process 254


Arunkumar Chinnasamy, Bioinformatics Institute, Singapore


Sudhanshu Patwardhan, Bioinformatics Institute, Singapore


Wing-Kin Sung, National University of Singapore, Singapore


Chapter XIII


Bayesian Network Approach to Estimate Gene Networks 269


Seiya Imoto, University of Tokyo, Japan


Satoru Miyano, University of Tokyo, Japan


Chapter XIV


Bayesian Network Modeling of Transcription Factor Binding Sites: A Tutorial 300


Vipin Narang, National University of Singapore, Singapore


Rajesh Chowdhary, National University of Singapore, Singapore


Ankush Mittal, Indian Institute of Technology, India


Wing-Kin Sung, National University of Singapore, Singapore


Chapter XV


Application of Bayesian Network in Learning Gene Network 319


Tie-Fei Liu, National University of Singapore, Singapore


Wing-Kin Sung, National University of Singapore, Singapore


Ankush Mittal, Indian Institute of Technology, India


About the Authors 342


Index 351
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2010-6-4 18:42:38
感谢楼主分享这么多经典的Bayesian书籍!!!
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2010-6-4 20:15:19
thanks! good one!
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2010-6-10 10:03:12
楼主,您好!我的论坛币不够,没法下载您的这本好书,但是又对这本书很感兴趣。您能不能发到我邮箱里啊?我的邮箱是:wangjunna_2008@126.com
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