JCST 2011 - Special Issue on Community Analysis and Information Recommendation

Website jcst.ict.ac.cn | Edit Freely

Category JCST 2011

Deadline: October 01, 2010 | Date: May 30, 2011

Venue/Country: Call for Papers, China

Updated: 2010-09-26 14:18:06 (GMT+9)

Call For Papers - CFP

(http://jcst.ict.ac.cn)

Special Issue on Community Analysis and Information Recommendation

Call for Papers

Over the last few years, we have witnessed a

tremendous growth in online social network

services (SNS), such as Facebook, Twitter, and

Del.icio.us, which greatly facilitate the

collaboration, sharing, and other interactions

between individuals. The term Web 2.0 has been

coined to embrace all those new collaborative

services or applications and also to indicate a

new “social” approach to generating and

distributing Web content, characterized by open

communication, decentralization of authority,

personalized information seeking or filtering,

and wisdom of crowd. On one hand, the

ever-increasing social network services provide

large-scale social data for the analysis of user

behavior, and then improving the existing

services. On the other hand, they also bring forth

more severe information overload and require

more flexible and robust computing platforms or

service paradigms.

Generally, social network services mainly focus

on the two kinds of user needs, social needs and

information needs. Community is the typical

outcome of users’ social need and has practically

become the brands of social network services.

The research on community has become an

important focus of social network analysis. As

the prevalence of SNS, numerous so-called

user-generated-content (UGC) are available at

the unprecedented level. UGC provides data for

the analysis and understanding for users’

behavior and thus is valuable to the

improvement of existing services. This brings

forth a great deal of research issues, including

query log analysis, folksonomy, and so on. As to

users’ information needs, information overload

poses a big challenge to the success of SNS. As

an important approach for information filtering,

recommendation is usually adopted in industrial

and academia. Differently from traditional

recommendation, social and economic factors

play a critical role in the social network services.

Another emerging direction for SNS is mobile

SNS, which transform the platform from Internet

to mobile environments. Finally, the enabling

computing platform, e.g., data centers, plays an

essential role in the success of SNS. For example,

Facebook will have 40TB new data added to

their database every week, and these data are

highly shared among users, how to build a reliable

and efficient data center to support the

fast growing of data and population is not only

an interesting but also a challenge faced by the

community.

This special issue shall concentrate on recent

research in these areas and thus solicits research

articles on community analysis and information

recommendation, including but not limited to:

? Evolution and Dynamics of information

network and social network

? Temporal and community evolution

? Social network analysis and community

analysis

? Social Network Services and Social-Oriented

Computing

? Mobile social network services

? Social reputation and recommendation

systems

? Context-aware and multi-dimensional

recommendation techniques

? Evaluation of recommendation approaches

? Innovative recommendation applications

Guest Editors:

Prof. Xue-Qi Cheng, Chinese Academy of Science, China

Prof. Weisong Shi, Wayne State University, USA

Prof. Tao Zhou, UESTC, China

Important Dates

Submission due: Oct 1, 2010

First round of reviews due: Jan 1, 2011

Revision and second round review: Apr 1, 2011

Final manuscripts ready for JCST: May/June 2011

Submission

Manuscripts should describe original research

that has not yet been published or currently

under review by other journals or conferences.

Papers must be in single-column format,

double-spaced, and use fonts no smaller than 11pt.

There is no page limit, but it is encouraged to

keep the length less than 25 pages. Manuscripts

must be submitted through the JCST electronic

submission system at http://jcst.ict.ac.cn

When submitting please select " Special Issue on Community Analysis

and Information Recommendation" in the Manuscript Type column.