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Streaming Similarity Search over one Billion Tweets using Parallel Locality-Sensitive Hashing

Summary: Parallel LSH for streaming similarity search on >1B tweets; scalable across nodes and cores. Innovations: cache-conscious hash tables, 2-level merge for construction, duplicate-elimination during querying, insert-optimized structures and streaming expiration, plus a performance model; yields 1–2.5 ms queries and ~8x speedups over basic LSH and inverted indexes. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10679
Venue
VLDB
Year
2013
Pagerank
7.9799783e-05
Overall Rank
2,870 | 80.04%
DOI
-

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