Doctoral Symposium

The Recommender Systems 2007 Doctoral Consortium provided an opportunity for doctoral students to explore and develop their research interests in an interdisciplinary workshop, under the guidance of a panel of distinguished research faculty. We invited students who feel they would benefit from this kind of feedback on their dissertation work to apply for this unique opportunity to share their work with students in a similar situation as well as senior researchers in the field. The strongest candidates were those who had an idea and an area, and had made some progress, but who were not so far along that they can no longer make changes. Typically, this means they had made their dissertation proposal, but still were about a year from completion.


  1. Provide a supportive setting for feedback on students’ current research and guidance on future research directions.
  2. Offer each student comments and fresh perspectives on their work from faculty and students outside their own institution.
  3. Promote the development of a supportive community of scholars and a spirit of collaborative research.
  4. Contribute to the conference goals through interaction with other researchers and conference events.


The Consortium has been held on October 18 (Thursday). About eight doctoral students and four faculty have been invited to participate. Student participants had their abstracts published in the conference proceedings and exhibited a poster of their work at the main conference.  All participants were expected to attend the entire Consortium, including a group dinner following. Each student presented his or her work to the group with substantial time allowed for discussion and questions by participating faculty and other students. Being accepted into the Consortium is an honor, and involves a commitment to giving and receiving thoughtful commentary with an eye towards shaping the field and upcoming participants in the field.

Accepted Students

  • Justin Donaldson: A Hybrid Social-Acoustic Recommendation System for Popular Music
  • Xin Fu: Evaluating Sources of Implicit Feedback in Web Searches
  • Fabiana Lorenzi: A Multiagent Knowledge-based Recommender Approach with Truth
  • Mike Radmacher: Elicitation of Profile Attributes by Transparent Communication
  • Nava Tintarev: Explanation of Recommendations
  • Riina Vuorikari: Can Social Information Retrieval Enhance the Discovery and Reuse of Digital Educational Content?


  • Loren Terveen, University of Minnesota, United States
  • Francesco Ricci, Free University of Bozen-Bolzano, Italy