Usage derived recommendations for a video digital library

نویسندگان

  • Johan Bollen
  • Michael L. Nelson
  • Gary Geisler
  • Raquel Araujo
چکیده

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. r 2006 Elsevier Ltd. All rights reserved.

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عنوان ژورنال:
  • J. Network and Computer Applications

دوره 30  شماره 

صفحات  -

تاریخ انتشار 2007