Jair Merlo, Accenture, Sao Paulo, Brazil Excerpts from full review posted Oct 12 2012 to Computing Reviews [Review #: CR140595 (1302-0087)] ...In spite of the spectrum of subjects and diversity of authors, the book's editors have been extremely successful in providing coherent and integrated content... After a thorough depiction of the theoretical state of the art in behavior modeling, chapter 4 offers a gold mine for practitioners: a semi-Markovian algorithm for user behavior analysis that is very easy to grasp, even for novices, and implemented in ActiveX... Part 4 continues to explore applications of behavior computing with a plethora of diverse cases that illustrate the importance of this novice discipline. The book provides valuable knowledge for both academia and industry.

• Preface.- Part I: Behavior Modeling.- Analyzing Behavior of the Influentials across Social Media.- Modeling and Analysis of Social Activity Process.- Behavior Representation and Management Making Use of the Narrative Knowledge Representation Language.- Semi-Markovian representation of User Behavior in Software Packages.- Part II: Behavior Analysis.- P-SERS: Personalized Social Event Recommender System.- Simultaneously Modeling Reply Networks and Contents to Generate User’s Profiles on Web Forum.- Information Searching Behavior Mining Based on Reinforcement Learning Models.- Estimating Conceptual Similarities using Distributed Representations and Extended Backpropagation.- Scoring and Predicting Risk Preferences.- An Introduction to Prognostic Search.- Part III: Behavior Mining.- Clustering Clues of Trajectories for Discovering Frequent Movement Behaviors.- Linking Behavioral Patterns to Personal Attributes through Data Re-Mining.- Mining Causality from Non-categorical Numerical Data.- A Fast Algorithm for Mining High Utility Itemsets.- Individual Movement Behavior in Secure Physical Environments: Modeling and Detection of Suspicious Activity.- A Behavioral Modeling Approach to Prevent Unauthorized Large-Scale Documents Copying from Digital Libraries.- Analyzing Twitter User Behaviors and Topic Trends by Exploiting Dynamic Rules.- Part IV: Behavior Applications.- Behavior Analysis of Telecom Data using Social Network Analysis.- Event Detection based on Call Detail Records.- Smart Phone: Predicting the Next Call.- A System with Hidden Markov Models and Guassian Mixture Models for 3D Handwriting Recognition on Handheld Devices using Accelerometers.- Medical Student’s Search Behavior: An Exploratory Survey.- An Evaluation Scheme of Software Testing Strategy.

Jair Merlo, Accenture, Sao Paulo, Brazil Excerpts from full review posted Oct 12 2012 to Computing Reviews [Review #: CR140595 (1302-0087)] ...In spite of the spectrum of subjects and diversity of authors, the book's editors have been extremely successful in providing coherent and integrated content... After a thorough depiction of the theoretical state of the art in behavior modeling, chapter 4 offers a gold mine for practitioners: a semi-Markovian algorithm for user behavior analysis that is very easy to grasp, even for novices, and implemented in ActiveX... Part 4 continues to explore applications of behavior computing with a plethora of diverse cases that illustrate the importance of this novice discipline. The book provides valuable knowledge for both academia and industry.

• Preface.- Part I: Behavior Modeling.- Analyzing Behavior of the Influentials across Social Media.- Modeling and Analysis of Social Activity Process.- Behavior Representation and Management Making Use of the Narrative Knowledge Representation Language.- Semi-Markovian representation of User Behavior in Software Packages.- Part II: Behavior Analysis.- P-SERS: Personalized Social Event Recommender System.- Simultaneously Modeling Reply Networks and Contents to Generate User’s Profiles on Web Forum.- Information Searching Behavior Mining Based on Reinforcement Learning Models.- Estimating Conceptual Similarities using Distributed Representations and Extended Backpropagation.- Scoring and Predicting Risk Preferences.- An Introduction to Prognostic Search.- Part III: Behavior Mining.- Clustering Clues of Trajectories for Discovering Frequent Movement Behaviors.- Linking Behavioral Patterns to Personal Attributes through Data Re-Mining.- Mining Causality from Non-categorical Numerical Data.- A Fast Algorithm for Mining High Utility Itemsets.- Individual Movement Behavior in Secure Physical Environments: Modeling and Detection of Suspicious Activity.- A Behavioral Modeling Approach to Prevent Unauthorized Large-Scale Documents Copying from Digital Libraries.- Analyzing Twitter User Behaviors and Topic Trends by Exploiting Dynamic Rules.- Part IV: Behavior Applications.- Behavior Analysis of Telecom Data using Social Network Analysis.- Event Detection based on Call Detail Records.- Smart Phone: Predicting the Next Call.- A System with Hidden Markov Models and Guassian Mixture Models for 3D Handwriting Recognition on Handheld Devices using Accelerometers.- Medical Student’s Search Behavior: An Exploratory Survey.- An Evaluation Scheme of Software Testing Strategy.

Jair Merlo, Accenture, Sao Paulo, Brazil Excerpts from full review posted Oct 12 2012 to Computing Reviews [Review #: CR140595 (1302-0087)] ...In spite of the spectrum of subjects and diversity of authors, the book's editors have been extremely successful in providing coherent and integrated content... After a thorough depiction of the theoretical state of the art in behavior modeling, chapter 4 offers a gold mine for practitioners: a semi-Markovian algorithm for user behavior analysis that is very easy to grasp, even for novices, and implemented in ActiveX... Part 4 continues to explore applications of behavior computing with a plethora of diverse cases that illustrate the importance of this novice discipline. The book provides valuable knowledge for both academia and industry.

• Preface.- Part I: Behavior Modeling.- Analyzing Behavior of the Influentials across Social Media.- Modeling and Analysis of Social Activity Process.- Behavior Representation and Management Making Use of the Narrative Knowledge Representation Language.- Semi-Markovian representation of User Behavior in Software Packages.- Part II: Behavior Analysis.- P-SERS: Personalized Social Event Recommender System.- Simultaneously Modeling Reply Networks and Contents to Generate User’s Profiles on Web Forum.- Information Searching Behavior Mining Based on Reinforcement Learning Models.- Estimating Conceptual Similarities using Distributed Representations and Extended Backpropagation.- Scoring and Predicting Risk Preferences.- An Introduction to Prognostic Search.- Part III: Behavior Mining.- Clustering Clues of Trajectories for Discovering Frequent Movement Behaviors.- Linking Behavioral Patterns to Personal Attributes through Data Re-Mining.- Mining Causality from Non-categorical Numerical Data.- A Fast Algorithm for Mining High Utility Itemsets.- Individual Movement Behavior in Secure Physical Environments: Modeling and Detection of Suspicious Activity.- A Behavioral Modeling Approach to Prevent Unauthorized Large-Scale Documents Copying from Digital Libraries.- Analyzing Twitter User Behaviors and Topic Trends by Exploiting Dynamic Rules.- Part IV: Behavior Applications.- Behavior Analysis of Telecom Data using Social Network Analysis.- Event Detection based on Call Detail Records.- Smart Phone: Predicting the Next Call.- A System with Hidden Markov Models and Guassian Mixture Models for 3D Handwriting Recognition on Handheld Devices using Accelerometers.- Medical Student’s Search Behavior: An Exploratory Survey.- An Evaluation Scheme of Software Testing Strategy.