We are pleased to invite you to participate in this premier annual event on research and applications of recommender technologies.

The 2nd ACM International Conference on Recommender Systems builds on the success of Recommenders 06 Summer School in Bilbao, Spain; and the 1st International Conference in Minneapolis, USA. In these events many members of the practitioner and research communities valued the rich exchange of ideas made possible by the shared plenary sessions. The 2nd International conference will promote the same close interaction among practitioners and researchers, reaching a wider range of participants including those from Europe and Asia. Published papers will go through a full peer review process. The conference proceedings, which are available both as bound volume and via the ACM Digital Library, are expected to be widely read and cited.

In addition to a regular technical program, there will be 2-3 tutorials covering the state-of-the-art of this domain, a doctoral consortium, and an industrial program comprising of panel discussions and a practice/industry-paper track. We also expect to have one keynote speaker who will address the major applications of recommendation technologies in industry.

Deadline for paper submission is May 18th, 2008.

Please stay tuned for further information on this conference.

Pearl Pu, General Chair, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
Bamshad Mobasher, Program Co-Chair, DePaul University, USA
Francesco Ricci, Program Co-Chair, Free University Bozen-Bolzano, Italy
Derek Bridge, Short Papers Chair, University College Cork, Ireland
Francisco Martin, Industry Program Co-Chair, Strands, Inc.
Shail Patel, Industry Program Co-Chair, Unilever UK
Lorraine McGinty, Publicity Chair, UCD Dublin, Ireland
Yuan Chun Shi, Asia Liaison, Tsinghua University, China
About Recommender Systems

Recommender systems are software applications that aim to support users in their decision-making while interacting with large information spaces. They recommend items of interest to users based on preferences they have expressed, either explicitly or implicitly. The ever-expanding volume and increasing complexity of information on the Web has therefore made such systems essential tools for users in a variety of information seeking or e-commerce activities. Recommender systems help overcome the information overload problem by exposing users to the most interesting items, and by offering novelty, surprise, and relevance. Recommender technology is hence the central piece of the information seeking puzzle. Major e-commerce sites such as Amazon and Yahoo are using recommendation technology in ubiquitous ways. Many new comers are on their way and entrepreneurs are competing in order to find the right approach to use this technology effectively.

Some people say that recommendation technology represents the new paradigm of search: interesting items find the user instead of the user explicitly searching for them. In an article published in CNN Money, entitled "The race to create a 'smart' Google", Fortune magazine writer Jeffrey M. O'Brien, writes:
The Web, they say, is leaving the era of search and entering one of discovery. What's the difference? Search is what you do when you're looking for something. Discovery is when something wonderful that you didn't know existed, or didn't know how to ask for, finds you.