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Recsplorer: Recommendation Algorithms Based on Precedence Mining

Summary: Introduces precedence mining to estimate future consumption from past behavior, enabling Recsplorer's suite of precedence-based recommendation algorithms. Unlike rating-based CF, it leverages global temporal precedence patterns and is evaluated on real transcripts and live user studies, showing improvements in temporally structured domains. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4236
Venue
SIGMOD
Year
2010
Pagerank
5.6335259e-05
Overall Rank
5,189 | 63.94%
DOI
-

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Rank Citing Paper Year Venue Pagerank
4,975 Challenging the Long Tail Recommendation 2012 VLDB 5.7854712e-05
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