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Distributed Evaluation of Top-k Temporal Joins

Summary: RTJ defines top-k ranked temporal joins with interval predicates and scoring. TKIJ uses offline time-granule endpoint statistics and online score bounds to balance reducers, minimize replication, and prune results in Map-Reduce, yielding strong n-ary RTJ performance. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5104
Venue
SIGMOD
Year
2016
Pagerank
4.4302523e-05
Overall Rank
8,857 | 38.45%
DOI
10.1145/2882903.2882912

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,510 Relevance Queries for Interval Data 2025 SIGMOD 4.1905499e-05
11,660 Top-k Queries over Digital Traces 2019 SIGMOD 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 14 of 14 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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