Joseph A. Konstan
Professor of Computer Science and Engineering
University of Minnesota
Nishikant Kapoor
Ph.D. Student, Computer Science
University of Minnesota
Sean M. McNee
Ph.D. Student, Computer and Information Sciences
University of Minnesota
John T. Butler
Director, Digital Library Development Laboratory
University of Minnesota
Recommender systems are tools that use ratings, opinions, or actions from a community to help individuals find information or products of interest to them. While recommenders have been most prominent in electronic commerce and entertainment, we have shown in prior research that the same techniques can be used to exploit citation data to help library users discover papers of interest. In this briefing, we will demonstrate technology and interfaces through which such recommendations can be used to help users build reading lists, enhance their bibliographies, and perform other tasks related to the use of a digital library. We also will present for discussion a variety of applications of recommender technology to serve library users, along with some of the key challenges that exist in realizing such applications. Finally, while all of our current work uses fully public data, we recognize the tremendous potential of incorporating personal bibliographies; accordingly, we plan to raise the issues of personal privacy, and engage in discussions about the nature of voluntary informed consent needed to ethically put such tools at the disposal of users.
Handout (PDF)
