Behavior computing : modeling, analysis, mining and decision
著者
書誌事項
Behavior computing : modeling, analysis, mining and decision
Springer, c2012
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
'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.
目次
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.
「Nielsen BookData」 より