Recommender systems have been recognized as a promising way to solve the information overload problem, whose main task is to find out what their users might like. Recent evidence demonstrates the significance of social influence and indicate that recommendations made by advanced techniques and algorithms are often less appreciated than those coming from our friends or acquaintances. The emergence of large-scale social network services, such as Facebook and Twitter, is facilitating the development of social recommendation. Beyond theoretical interests, academic studies on social recommender systems can immediately find industrial applications.
We seek high-qualified, original submissions of reports on research covering all the aspects of designs, techniques, algorithms, experiments, and empirical analyses on social recommender systems.
The topics include but are not limited to the following:
Important Dates
Submission Guidelines
Authors are invited to submit their manuscript in LNCS/LNAI style (please see this page), maximum 10 pages. Paper should be submitted in PDF form via ISMIS 2012 Online Submission System. The submitted papers will be reviewed by the session's program committee. For information about the main conference, 20th International Symposium on Methodologies for Intelligent Systems: ISMIS-12, see the conference web page.
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