Behavior Computing: Modeling, Analysis, Mining and Decision

✍ Scribed by Nitin Agarwal, Shamanth Kumar, Huiji Gao, Reza Zafarani, Huan Liu (auth.), Longbing Cao, Philip S. Yu (eds.)

• Publisher: Springer-Verlag London
• Year: 2012
• Tongue: English
• Leaves: 371
• Edition: 1
• Category: Library

✦ Synopsis

'Behavior' is an increasingly important concept in the scientific, societal, economic, cultural, political, military, living and virtual worlds. Behavior computing, or behavior informatics, consists of methodologies, techniques and practical tools for examining and interpreting behaviours in these various worlds. Behavior computing contributes to the in-depth understanding, discovery, applications and management of behavior intelligence. With contributions from leading researchers in this emerging field Behavior Computing: Modeling, Analysis, Mining and Decision includes chapters on: representation and modeling behaviors; behavior ontology; behaviour analysis; behaviour pattern mining; clustering complex behaviors; classification of complex behaviors; behaviour impact analysis; social behaviour analysis; organizational behaviour analysis; and behaviour computing applications. Behavior Computing: Modeling, Analysis, Mining and Decision provides a dedicated source of reference for the theory and applications of behavior informatics and behavior computing. Researchers, research students and practitioners in behavior studies, including computer science, behavioral science, and social science communities will find this state of the art volume invaluable.

✦ Table of Contents

Front Matter....Pages I-XVI
Front Matter....Pages 1-1
Analyzing Behavior of the Influentials Across Social Media....Pages 3-19
Modeling and Analysis of Social Activity Process....Pages 21-35
Behaviour Representation and Management Making Use of the Narrative Knowledge Representation Language....Pages 37-56
Semi-Markovian Representation of User Behavior in Software Packages....Pages 57-68
Front Matter....Pages 69-69
P-SERS: Personalized Social Event Recommender System....Pages 71-89
Simultaneously Modeling Reply Networks and Contents to Generate User’s Profiles on Web Forum....Pages 91-108
Information Searching Behavior Mining Based on Reinforcement Learning Models....Pages 109-126
Estimating Conceptual Similarities Using Distributed Representations and Extended Backpropagation....Pages 127-142
Scoring and Predicting Risk Preferences....Pages 143-163
An Introduction to Prognostic Search....Pages 165-175
Front Matter....Pages 177-177
Clustering Clues of Trajectories for Discovering Frequent Movement Behaviors....Pages 179-196
Linking Behavioral Patterns to Personal Attributes Through Data Re-Mining....Pages 197-214
Mining Causality from Non-categorical Numerical Data....Pages 215-227
A Fast Algorithm for Mining High Utility Itemsets....Pages 229-240
Individual Movement Behaviour in Secure Physical Environments: Modeling and Detection of Suspicious Activity....Pages 241-253
A Behavioral Modeling Approach to Prevent Unauthorized Large-Scale Documents Copying from Digital Libraries....Pages 255-265
Analyzing Twitter User Behaviors and Topic Trends by Exploiting Dynamic Rules....Pages 267-287
Front Matter....Pages 289-289
Behavior Analysis of Telecom Data Using Social Networks Analysis....Pages 291-303
Event Detection Based on Call Detail Records....Pages 305-316
Smart Phone: Predicting the Next Call....Pages 317-325
Front Matter....Pages 289-289
A System with Hidden Markov Models and Gaussian Mixture Models for 3D Handwriting Recognition on Handheld Devices Using Accelerometers....Pages 327-336
Medical Students’ Search Behaviour: An Exploratory Survey....Pages 337-351
An Evaluation Scheme of Software Testing Strategy....Pages 353-361
Back Matter....Pages 363-374

✦ Subjects

Models and Principles; Data Mining and Knowledge Discovery; Information Storage and Retrieval; Information Systems Applications (incl. Internet); Artificial Intelligence (incl. Robotics); Simulation and Modeling