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)
Incoming Non-self Citations Over Time
Authors
- 1. Aditya Parameswaran (Stanford University)
- 2. Georgia Koutrika (IBM)
- 3. Benjamin Bercovitz (Stanford University)
- 4. Hector Garcia-Molina (Stanford University)
BibTeX Citation
@inproceedings{parameswaran_sigmod10,
title = {{Recsplorer: Recommendation Algorithms Based on Precedence Mining}},
author = {Parameswaran, Aditya and Koutrika, Georgia and Bercovitz, Benjamin and Garcia-Molina, Hector},
series = {{SIGMOD} '10},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1807167.1807179},
url = {https://dl.acm.org/doi/10.1145/1807167.1807179},
year = {2010}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,272 | Challenging the Long Tail Recommendation | 2012 | VLDB | 6.7911017e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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|---|
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