Skip-and-Prune: Cosine-based Top-K Query Processing for Efficient Context-Sensitive Document Retrieval
Summary: Skip-and-Prune (SnP): top-k for cosine-based, non-monotonic scoring in context-aware retrieval. SnP matches inverted-file/full-scan precision, yet is orders of magnitude faster than naive top-k or accumulator-based approaches. (summarized by gpt-5-nano on Feb 09 2026)
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8 | Optimal Aggregation Algorithms for Middleware [Extended Abstract] | 2001 | PODS | 0.0015436578 |
| 262 | Efficient Progressive Skyline Computation | 2001 | VLDB | 0.00029962961 |
| 436 | XSEarch: A Semantic Search Engine for XML | 2003 | VLDB | 0.00023264416 |
| 673 | Supporting Top-k Join Queries in Relational Databases | 2003 | VLDB | 0.00018325667 |
| 1,140 | EntityRank: Searching Entities Directly and Holistically | 2007 | VLDB | 0.00013709412 |
| 1,805 | Top-k Query Evaluation with Probabilistic Guarantees | 2004 | VLDB | 0.00010479371 |
| 6,054 | Ranking Objects by Exploiting Relationships: Computing Top-K over Aggregation | 2006 | SIGMOD | 5.2310615e-05 |
| 6,292 | Ad-Hoc Aggregations of Ranked Lists in the Presence of Hierarchies | 2008 | SIGMOD | 5.1209778e-05 |
| 7,133 | Anytime Measures for Top-k Algorithms | 2007 | VLDB | 4.8175888e-05 |
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