rsweb 2012 - 4th Workshop on Recommender Systems & the Social Web
Topics/Call fo Papers
4th Workshop on Recommender Systems & the Social Web
in conjunction with ACM RecSys 2012
Dublin, Ireland, September 9, 2012
http://ls13-www.cs.uni-dortmund.de/homepage/rsweb2...
Submission Deadline: June 8, 2012
The exponential growth of the Social Web poses both challenges and new opportunities for recommender systems research. The Social Web has turned information consumers into active contributors creating massive amounts of information. Finding relevant and interesting content at the right time and in the right context is challenging for existing recommender approaches. At the same time, social systems by their very nature encourage interaction among users and with a variety of resources, thus generating new sources of knowledge for recommender systems. Users of social media on the Web often explicitly provide personal information or implicitly express preferences through their interactions with other users or with resources (e.g. tagging, friending, rating, commenting, etc.).
New application areas for recommender systems emerge with the popularity of the Social Web. Recommenders can not only be used to sort and filter Web 2.0 and social network information, they can also support users in the information sharing process, e.g., by recommending suitable tags during folksonomy development. There are also opportunities for novel recommender applications on the Social Web that directly involve humans in the recommendation process, for example, users or groups making recommendations to other users, or online multi-user games leading to recommendations.
These various new sources of knowledge can be leveraged to improve recommendation techniques and develop new strategies which focus on social recommendation. This social layer can also be used as evidence on which to infer relationships and trust levels between users for recommendation generation.
Recommender systems technologies can assist social systems through increasing adoption and participation and sustaining membership. Through targeted and timely intervention which stimulates traffic and interaction, recommender systems technology can play its role in sustaining the success of the Social Web.
The goal of this workshop is to bring together researcher and practitioners to explore, discuss, and understand challenges and new opportunities for recommender systems and the Social Web. Original contributions are solicited in all aspects of recommendation on the Social Web, including, but not limited to the following areas:
* Social network and folksonomy development: Recommending friends, tags, bookmarks, blogs, music, communities etc.
* Leveraging models of user behavior on the Social Web for recommendation
* Recommender systems mash-ups, intelligent user interfaces, rich media recommender systems
* Collaborative knowledge authoring, collective intelligence
* Topic emergence and evolution on the Social Web and their role in recommendation process
* Recommender applications involving users or groups directly in the recommendation process
* Exploiting folksonomies, social network information, user interactions, and communities in the recommendation process
* The role of context in Social Web recommendation
* Trust and reputation aware social recommendations
* Semantic Web recommender systems, use of ontologies or microformats
* Empirical evaluation of social recommender techniques
* Case studies and novel fielded social recommender applications
* Economy of community-based systems: Using recommenders to encourage users to contribute and sustain participation
* Social recommender systems in the enterprise
* Recommendation for groups
IMPORTANT DATES
* June 8, 2012: Paper/position statement submission due
* June 22, 2012: Notification of workshop submitters
* July 3, 2012: Camera-ready workshop papers due
* September 9, 2012: Workshop held
PAPER SUBMISSION
We solicit short and long papers as well as research demos on all aspects of recommender systems in the Social Web. Papers should be formatted according to the style guide of RecSys 2012. (Please see: http://recsys.acm.org/2012/submission.html).
Long papers present original research work and can be of up to 8 pages in length. Short papers report on work in progress and can have up to 4 pages. Presenters of demo systems are asked to submit short papers describing their system.
Papers should be submitted in PDF format through the EasyChair system at http://www.easychair.org/conferences/?conf=rsweb12.
Paper selection will be based on a peer review process; there will be no blind review process - author names and affiliations should be included in the paper.
At least one author of each accepted paper must register for the workshop. Information about registration is provided at the RecSys 2012 Web page: http://recsys.acm.org/2012/.
Accepted papers will be published via ACM Digital Library.
Send question and inquiries to: rsweb2012-AT-ls13.cs.uni-dortmund.de
Organizers
- Bamshad Mobasher, School of Computing, DePaul University, USA
- Dietmar Jannach, Department of Computer Science, TU Dortmund, Germany
- Werner Geyer, IBM Research, Cambridge, MA, USA
- Andreas Hotho, University of Würzburg, Germany
in conjunction with ACM RecSys 2012
Dublin, Ireland, September 9, 2012
http://ls13-www.cs.uni-dortmund.de/homepage/rsweb2...
Submission Deadline: June 8, 2012
The exponential growth of the Social Web poses both challenges and new opportunities for recommender systems research. The Social Web has turned information consumers into active contributors creating massive amounts of information. Finding relevant and interesting content at the right time and in the right context is challenging for existing recommender approaches. At the same time, social systems by their very nature encourage interaction among users and with a variety of resources, thus generating new sources of knowledge for recommender systems. Users of social media on the Web often explicitly provide personal information or implicitly express preferences through their interactions with other users or with resources (e.g. tagging, friending, rating, commenting, etc.).
New application areas for recommender systems emerge with the popularity of the Social Web. Recommenders can not only be used to sort and filter Web 2.0 and social network information, they can also support users in the information sharing process, e.g., by recommending suitable tags during folksonomy development. There are also opportunities for novel recommender applications on the Social Web that directly involve humans in the recommendation process, for example, users or groups making recommendations to other users, or online multi-user games leading to recommendations.
These various new sources of knowledge can be leveraged to improve recommendation techniques and develop new strategies which focus on social recommendation. This social layer can also be used as evidence on which to infer relationships and trust levels between users for recommendation generation.
Recommender systems technologies can assist social systems through increasing adoption and participation and sustaining membership. Through targeted and timely intervention which stimulates traffic and interaction, recommender systems technology can play its role in sustaining the success of the Social Web.
The goal of this workshop is to bring together researcher and practitioners to explore, discuss, and understand challenges and new opportunities for recommender systems and the Social Web. Original contributions are solicited in all aspects of recommendation on the Social Web, including, but not limited to the following areas:
* Social network and folksonomy development: Recommending friends, tags, bookmarks, blogs, music, communities etc.
* Leveraging models of user behavior on the Social Web for recommendation
* Recommender systems mash-ups, intelligent user interfaces, rich media recommender systems
* Collaborative knowledge authoring, collective intelligence
* Topic emergence and evolution on the Social Web and their role in recommendation process
* Recommender applications involving users or groups directly in the recommendation process
* Exploiting folksonomies, social network information, user interactions, and communities in the recommendation process
* The role of context in Social Web recommendation
* Trust and reputation aware social recommendations
* Semantic Web recommender systems, use of ontologies or microformats
* Empirical evaluation of social recommender techniques
* Case studies and novel fielded social recommender applications
* Economy of community-based systems: Using recommenders to encourage users to contribute and sustain participation
* Social recommender systems in the enterprise
* Recommendation for groups
IMPORTANT DATES
* June 8, 2012: Paper/position statement submission due
* June 22, 2012: Notification of workshop submitters
* July 3, 2012: Camera-ready workshop papers due
* September 9, 2012: Workshop held
PAPER SUBMISSION
We solicit short and long papers as well as research demos on all aspects of recommender systems in the Social Web. Papers should be formatted according to the style guide of RecSys 2012. (Please see: http://recsys.acm.org/2012/submission.html).
Long papers present original research work and can be of up to 8 pages in length. Short papers report on work in progress and can have up to 4 pages. Presenters of demo systems are asked to submit short papers describing their system.
Papers should be submitted in PDF format through the EasyChair system at http://www.easychair.org/conferences/?conf=rsweb12.
Paper selection will be based on a peer review process; there will be no blind review process - author names and affiliations should be included in the paper.
At least one author of each accepted paper must register for the workshop. Information about registration is provided at the RecSys 2012 Web page: http://recsys.acm.org/2012/.
Accepted papers will be published via ACM Digital Library.
Send question and inquiries to: rsweb2012-AT-ls13.cs.uni-dortmund.de
Organizers
- Bamshad Mobasher, School of Computing, DePaul University, USA
- Dietmar Jannach, Department of Computer Science, TU Dortmund, Germany
- Werner Geyer, IBM Research, Cambridge, MA, USA
- Andreas Hotho, University of Würzburg, Germany
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Last modified: 2012-05-02 23:25:22