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

@article{Sundaram2013StreamingSS,
  title={Streaming Similarity Search over one Billion Tweets using Parallel Locality-Sensitive Hashing},
  author={Narayanan Sundaram and Aizana Turmukhametova and Nadathur Satish and Todd Mostak and Piotr Indyk and Samuel Madden and Pradeep Dubey},
  journal={PVLDB},
  year={2013},
  volume={6},
  pages={1930-1941}
}
Finding nearest neighbors has become an important operation on databases, with applications to text search, multimedia indexing, and many other areas. One popular algorithm for similarity search, especially for high dimensional data (where spatial indexes like kdtrees do not perform well) is Locality Sensitive Hashing (LSH), an approximation algorithm for finding similar objects. In this paper, we describe a new variant of LSH, called Parallel LSH (PLSH) designed to be extremely efficient… CONTINUE READING
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