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ADMI 2016 : The Eleventh International Workshop on Agents and Data Mining InteractionConference Series : Agents and Data Mining Interaction | |||||||||||||||
Link: http://admi16.agentmining.org/ | |||||||||||||||
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Call For Papers | |||||||||||||||
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ADMI 2016 @ AAMAS 2016 ---------------------- The Eleventh International Workshop on Agents and Data Mining Interaction (ADMI-16) Singapore, 9-13 May, 2016 http://admi16.agentmining.org/ Held in conjunction with fifteenth International Joint Conference on AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (AAMAS-2016) http://sis.smu.edu.sg/aamas2016 ---------------- Important dates: ---------------- - Electronic submission of full papers: February 15, 2016 - Notification of paper acceptance: March 07, 2016 - Camera-ready copies of accepted papers: March 10, 2016 - AAMAS-2016 workshop: May 9-10, 2016 Scope The ADMI workshop provides a premier forum for sharing research and engineering results, as well as potential challenges and prospects encountered in the respective communities and the coupling between agents and data mining. The workshop welcomes theoretical work and applied dissemination aiming to: (1) explore the integration of agents and data mining towards a super-intelligent system; (2) discuss existing results, new problems, challenges and impact of integration of agent and data mining technologies and (3) identify challenges and directions for future research and development on the synergy between agents and data mining. Particularly, ADMI’ 16 will focus on the theme, namely Data-driven Agent Systems, and concentrate on the integration of emerging techniques like social computing, agent behaviorally modeling, big data and cloud computing. The workshop encourages submissions on, but not limited to: 1. Data-driven decision making and planning 2. Data-driven reasoning and learning 3. Data-driven agent interaction and coordination 4. Data-driven personalized agents 5. Data-driven multiagent simulation 6. Agent behavior learning 7. Agent and social networks 8. Agent-based methods and tools for big data analysis 9. Big data, cloud computing and agent simulation 10. Applications of data-driven agent systems Tentative Program: - Two Invited Talks - Presentation of 10-12 papers - One Panel Discussion ------------------------ Submission Instructions: ------------------------ Please follow the Springer LNAI formats. Papers are to be submitted through the EasyChair Conference System website EasyChair: https://easychair.org/conferences/?conf=admi2016 --------------------- Workshop publication: --------------------- 1. The ADMI-16 Proceedings will be published by Springer as a volume of LNAI series. 2. The most ADMI “visionary paper” will be published by Springer in a book under LNAI - Hot Topics series. The book will be a compilation of the most visionary papers of the AAMAS-2016 Workshops. 3. The best ADMI workshop paper will be published by Springer in a book under the Communications in Computer and Information Science (CCIS) series. The book will be a compilation of the best papers of the AAMAS-2016 Workshops. 4. A number of selected papers will be recommended to a special issue in International Journal of Data Science and Analytics. Workshop General Co-Chairs: - Philip S. Yu, University of Illinois at Chicago, USA - Longbing Cao, University of Technology Sydney, Australia Workshop Program Co-Chairs: - Yifeng Zeng, Teesside University, United Kingdom - Yingke Chen, Sichuan University, China - Marek Grzes, University of Kent, United Kingdom - Yinghui Pan, Jiangxi Finance and Economic University, China - Matteo Leonetti, The University of Texas at Austin, USA Workshop Organizing Co-chairs: - Vladimir Gorodetsky, Russian Academy of Sciences, Russia - Andreas L. Symeonidis, Aristotle University of Thessaloniki, Greece Workshop Submission Chair: - Ross Conroy, Teesside University, United Kingdom Supported by: Agent-Mining Interaction and Integration Special Interest Group (AMII-SIG) http://www.agentmining.org Primary Contact: - Yifeng Zeng, Teesside University, United Kingdom, Y.Zeng@tees.ac.uk |
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