Database Paper Browser

Back to papers

RecBench: Benchmarks for Evaluating Performance of Recommender System Architectures

Summary: Defines RecBench benchmarks for evaluating DBMS-based vs hand-built recommender architectures. Evaluates MultiLens vs RecStore on MovieLens 10M and Netflix 100M, showing hand-built excels in model-building and pure recommendations, while DBMS-based shines in filtered/hybrid tasks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10319
Venue
VLDB
Year
2011
Pagerank
4.1945683e-05
Overall Rank
12,211 | 15.05%
DOI
-

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers