Agents and data mining interaction : 9th International Workshop, ADMI 2013, Saint Paul, MN, USA, May 6-7, 2013, revised selected papers / edited by Longbing Cao [and five others].Material type: TextSeries: Serienbezeichnung | Lecture notes in computer science. Lecture notes in artificial intelligence ; ; 8316. | LNCS sublibrary. SL 7, Artificial intelligence.Publisher: Berlin : Springer, 2014Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642551925; 3642551920; 3642551912; 9783642551918Subject(s): Intelligent agents (Computer software) -- Congresses | Data mining -- Congresses | Data mining | Intelligent agents (Computer software)Genre/Form: Electronic books. | Ebook. | Conference papers and proceedings. Additional physical formats: Print version:: Agents and data mining interactionDDC classification: 006.3 LOC classification: QA76.76.I58Online resources: Click here to access online
|Item type||Current library||Collection||Call number||Status||Date due||Barcode||Item holds|
Revised conference papers.
Includes bibliographical references and author index.
This book constitutes the thoroughly refereed and revised selected papers from the 9th International Workshop on Agents and Data Mining Interaction, ADMI 2013, held in Saint Paul, MN, USA in May 2013. The 10 papers presented in this volume were carefully selected for inclusion in the book and are organized in topical sections named agent mining and data mining.
Print version record.
Using Dynamic Bayesian Networks to Model User-Experience -- Multi-Agent Joint Learning from Argumentation -- Towards Mining Norms in Open Source Software Repositories -- The Recognition of Multiple Virtual Identities Association Based on Multi-Agent System -- Redundant Feature Selection for Telemetry Data -- Mining Emerging Patterns of PIU from Computer-Mediated Interaction Events -- Learning Heterogeneous Coupling Relationships between Non-IID Terms -- Learning the Hotness of Information Discussions with Multi-Dimensional Hawkes Processes -- A Spectral Clustering Algorithm Based on Hierarchical Method -- Transitive Identity Mapping using Force-Based Clustering.