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Final CFP: IEEE Intelligent Systems, Special Issue on Social Learning

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  • Nathan N. Liu
    [Please accept our apologies if you have received multiple copies of this CFP] IEEE Intelligent Systems Call for Papers: Special Issue on Social Learning
    Message 1 of 1 , Sep 30, 2009
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      [Please accept our apologies if you have received multiple copies of this CFP]

      IEEE Intelligent Systems

      Call for Papers: Special Issue on Social Learning

      (http://www.cse.ust.hk/~nliu/cfp_sl.htm)

      ************************************************************************************************************



      In recent years, the social Web has shown tremendous growth, as the

      World Wide Web has transformed into a social platform for
      communication, information sharing and collaboration between Web
      users. Social learning is concerned with the principles,
      methodologies, techniques, tools, and applications of machine learning
      and knowledge discovery from/to social activities.



      An important ingredient of the social Web is machine learning, which
      faces several new challenges in the social Web setting. First, the
      social Web allows users in different places to contribute the content
      at different times in an entirely decentralized fashion, resulting in
      multiple inconsistent and conflicting views on matters such as the
      different tags assigned to the same Web. Second, social Web data cover
      a vast number of heterogeneous entities and distinct feature
      representations. Finally, the social Web is a highly dynamic in
      nature. We call learning on the social Web ‘Social Learning’.



      This IEEE Intelligent Systems special issue seeks articles related to
      all aspects of social learning. We solicit high-quality research
      papers on challenging research issues and state-of-the-art theories,
      techniques and applications. We invite submissions including, but not
      limited to, the following topics:



      -         Learning about group formation and evolution

      -         Social network analysis and mining

      -         Group interaction and collaboration

      -         Influence process and recognition

      -         Trust and reputation

      -         Opinion extraction and trend detection

      -         Expertise modeling and matching

      -         Multiple learner systems in social environment

      -         Exploitation of unannotated social Web data

      -         Ambiguity resolving on the social Web

      -         Knowledge extraction and management from social Web

      -         Use of the social Web data for different AI tasks

      -         Click log mining and user modeling

      -         Agent and Multi-agent system on the Web

      -         Model and analysis complexity

      -         Data collection and benchmarks

      -         Metrics and evaluation

      -         Personalization, security and privacy





      Submission Guidelines

      ***********************

      Submissions due for review: November 7, 2009



      Submissions should be 3,500 to 7,500 words (counting a standard figure

      or table as 200 words) and should follow the magazine style and

      presentation guidelines (see

      www.computer.org/portal/pages/intelligent/mc/author.html).

      References should be limited to 10 citations. To submit a manuscript,

      access the IEEE Computer Society Web-based system, Manuscript Central,

      at ( https://mc.manuscriptcentral.com/cs-ieee ).





      Questions and Further Information:

      **********************

      Contact Guest Editors

      *Nathan Nan Liu, Hong Kong University of Science and Technology, Hong
      Kong (nliu@...)

      Qiang Yang, Hong Kong University of Science and Technology, Hong Kong
      (qyang@...)

      Zhi-Hua Zhou, Nanjing University, Nanjing, China (zhouzh@...)

      Wei Li, Beihang University (BUAA), Beijing, China (liwei@...)

      Wen-Ji Mao, Chinese Academy of Sciences, Beijing, China (wenji.mao@...)
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