Database Paper Browser

Back to papers

A Social Network Database that Learns How to Answer Queries

Summary: Introduce a social-network DB that makes social predicates (importance, relevance) first-class query primitives and embeds machine learning in the query processor to pick and tune predicate implementations and rankings. Emphasizes adaptive, query- and user-aware optimization. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
197
Venue
CIDR
Year
2013
Pagerank
4.1945683e-05
Overall Rank
12,025 | 16.35%
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 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
7,998 Data Management for Social Networking 2016 PODS 4.6101889e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1,870 Flexible Queries over Semistructured Data 2001 PODS 0.00010263799
4,105 SocialScope: Enabling Information Discovery on Social Content Sites 2009 CIDR 6.4478049e-05
Previous Page 1 / 1 Next

Semantically Similar Papers