Scalable Semantic Querying of Text
Summary: KOKO: scalable semantic extraction using a dual-structure extraction language over surface text and dependency parses. Uses multi-indexing and heuristics to scale extractions, with compact indices and fast performance on large corpora. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Xiaolan Wang
- 2. Aaron Feng
- 3. Behzad Golshan
- 4. Alon Halevy
- 5. George Mihaila
- 6. Hidekazu Oiwa
- 7. Wang-Chiew Tan
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,347 | Adaptive Rule Discovery for Labeling Text Data | 2021 | SIGMOD | 5.5560452e-05 |
| 13,324 | Koko: A System for Scalable Semantic Querying of Text | 2018 | VLDB | - |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 61 | DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases | 1997 | VLDB | 0.00064329285 |
| 287 | Declarative Information Extraction Using Datalog with Embedded Extraction Predicates | 2007 | VLDB | 0.00028971272 |
| 6,919 | Efficient Indexing and Querying over Syntactically Annotated Trees | 2012 | VLDB | 4.8925595e-05 |
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