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: 4235
Venue: SIGMOD
Year: 2010
Pagerank: 5.6308806e-05
Overall Rank: 5,204 | 63.80%
DOI: -

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
5,015	Challenging the Long Tail Recommendation	2012	VLDB	5.7584513e-05

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank

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