GUEST EDITORS
John Riedl, University of Minnesota
Barry Smyth, University College, Dublin

Recommender systems are changing the way people interact with the Web. From e-commerce sites like Amazon.com to news and information sites like digg and slashdot, recommenders help people choose between diverse products and complex information, by providing a more personalized information access experience. While much of the published research on recommenders has focused on the algorithms that power the recommendation process, many research challenges remain, especially when it comes to the applications, interfaces and social implications of recommenders.

This special issue of ACM Transactions on the Web aims to gather a collection of high quality contributions that reflect recent innovations in the field of Web-based recommender systems. Papers may focus on novel Web interfaces for recommenders, on emerging applications of recommenders, or on the ways recommenders fit into the Social Web.

Particular areas of interest include, but are not limited to:

Applications of Recommenders on the Web: Recommenders on the Web, including the mobile Web and e-commerce; recommenders and community, including group recommenders, recommenders to support social networking, and techniques for leveraging the social graph in forming recommendations.

Recommendation Interfaces: Novel recommendation interfaces, including Web, mobile, and Web2.0; emerging interface technologies, including haptic interfaces, group interfaces, and public-displays; the role of explanations in recommender systems; evaluating recommendation interfaces through user studies and other HCI approaches.

The Social Implications of Recommender Systems: User privacy in recommender systems; privacy-preserving recommendation techniques; security and data protection; the robustness of recommender systems (e.g., to recommendation spam); techniques for detecting and coping with malicious users; on the role of trust in recommender systems; computational models of trust for recommender applications.

Recommender Algorithms for the Web: Novel algorithms especially suited to Web applications; evaluation techniques for algorithms that effectively predict performance in practice; hybrid collaborative and content-based recommenders; conversational recommenders.

Prospective authors, please submit your paper according to the directions on the ACM TWEB Web site following the content and formatting guidelines available at http://www.acm.org/tweb/author.html . There you can also find detailed information about the ACM TWEB review process. When submitting your paper, please mention that it is to be considered for the special issue on Recommenders on the Web. In addition, please send a copy of your paper to riedl (at) cs (dot) umn (dot) edu and barry.smyth (at) ucd (dot) ie with the subject line "TWeb: Recommenders on the Web".

IMPORTANT DATES

Papers due: September 15, 2008
Author notification: January 30, 2009
Revised versions of accepted papers due: March 16, 2009 (all accepted papers expected to undergo a minor set of revisions)
Final materials for publication due: May 1, 2009
Special issue published: November 2009