An Information-Theoretic Study on Aggregate Responses
Summary: An information-theoretic framework for aggregate responses over quantified concepts, balancing conciseness (expression length) and preciseness (entropy). One-level taxonomies admit efficient optimal expressions; for broader taxonomies, heuristics achieve strong solutions with good empirical results. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chung-Dak Shum
- 2. Richard Muntz
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 381 | Querying Database Knowledge | 1990 | SIGMOD | 0.00024892227 |
| 523 | Recovering Information from Summary Data | 1997 | VLDB | 0.00021101376 |
| 6,011 | Data Vocalization with CiceroDB | 2019 | CIDR | 5.2365238e-05 |
| 6,434 | A Multi-Resolution Relational Data Model | 1992 | VLDB | 5.0556181e-05 |
| 9,185 | Using Integrity Constraints to Provide Intensional Answers to Relational Queries | 1989 | VLDB | 4.3771771e-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.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|
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