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)
Incoming Non-self Citations Over Time
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Authors
- 1. Sara Cohen
- 2. Lior Ebel
- 3. Benny Kimelfeld
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,926 | Data Management for Social Networking | 2016 | PODS | 4.6107647e-05 |
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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 |
|---|---|---|---|---|
| 1,873 | Flexible Queries over Semistructured Data | 2001 | PODS | 0.00010255165 |
| 4,104 | SocialScope: Enabling Information Discovery on Social Content Sites | 2009 | CIDR | 6.4428325e-05 |
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