Usage derived recommendations for a video digital library

Authors:
Johan Bollen;Michael L. Nelson;Gary Geisler;Raquel Araujo
Affiliations:
Research Library, Los Alamos National Laboratory, Los Alamos, NM 87545, USA and Department of Computer Science, Old Dominion University, 4700 Elkhorn Avenue, Norfolk, VA 23529, USA;Department of Computer Science, Old Dominion University, 4700 Elkhorn Avenue, Norfolk, VA 23529, USA;School of Information, University of Texas, Austin, TX 78712, USA;Department of Computer Science, Old Dominion University, 4700 Elkhorn Avenue, Norfolk, VA 23529, USA
Venue:
Journal of Network and Computer Applications
Year:
2007

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Abstract

We describe a minimalist methodology to develop usage-based recommender systems for multimedia digital libraries. A prototype recommender system based on this strategy was implemented for the Open Video Project, a digital library of videos that are freely available for download. Sequential patterns of video retrievals are extracted from the project's web download logs and analyzed to generate a network of video relationships. A spreading activation algorithm locates video recommendations by searching for associative paths connecting query-related videos. We evaluate the performance of the resulting system relative to an item-based collaborative filtering technique operating on user profiles extracted from the same log data.