Love-at-First-Sight: First Answers Without the Awkward Silence in Big Knowledge Graphs
Summary: Introduces first-sight summaries (FSS) for KG/SPARQL exploration: log-driven summaries that return initial answers fast under budget, instead of waiting on costly coarse queries. Provides exact/approximate construction algorithms with guarantees, yielding up to 100x latency cuts over endpoints. (summarized by gpt-5.4-mini on May 27 2026)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 555 | An Analytical Study of Large SPARQL Query Logs | 2018 | VLDB | 0.00016655415 |
| 3,305 | A Formal Perspective on the View Selection Problem | 2001 | VLDB | 7.6052684e-05 |
| 5,633 | Graph-Aware, Workload-Adaptive SPARQL Query Caching | 2015 | SIGMOD | 6.2047208e-05 |
| 6,217 | X2Q: Your Personal Example-based Graph Explorer | 2018 | VLDB | 6.01306e-05 |
| 8,394 | Knowledge Graph Exploration Systems: are we lost? | 2022 | CIDR | 5.4958075e-05 |
| 8,400 | View Selection over Knowledge Graphs in Triple Stores | 2021 | VLDB | 5.4958075e-05 |
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