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Usage derived recommendations for a video digital library
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DOI：10.1016/j.jnca.2005.12.009.png)
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摘要
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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. (C) 2006 Elsevier Ltd. All rights reserved.
Keyword:
usage analysis
recommender systems video.
open video project
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