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IEEE Intelligent Systems 2010 : Final CFP: IEEE Intelligent Systems, Special Issue on Social Learning


When N/A
Where N/A
Abstract Registration Due Apr 1, 2010
Submission Deadline Nov 3, 2009
Notification Due Dec 30, 2009
Final Version Due Feb 1, 2010
Categories    computer science   artificial intelligence   machine learning   data mining

Call For Papers

IEEE Intelligent Systems

Call for Papers: Special Issue on Social Learning



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

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

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

at ( ).

Questions and Further Information:


Contact Guest Editors

*Nathan Nan Liu, Hong Kong University of Science and Technology, Hong
Kong (

Qiang Yang, Hong Kong University of Science and Technology, Hong Kong

Zhi-Hua Zhou, Nanjing University, Nanjing, China (

Wei Li, Beihang University (BUAA), Beijing, China (

Wen-Ji Mao, Chinese Academy of Sciences, Beijing, China (

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