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When Hashes Met Wedges : A Distributed Algorithm for Fin..:

, In: Proceedings of the 26th International Conference on World Wide Web,

Sharma, Aneesh ; Seshadhri, C. ; Goel, Ashish - p. 431-440 , 2017

Link: https://dl.acm.org/doi/10.1145/3038912.3052633

RT 
T1 <cTitle>Proceedings of the 26th International Conference on World Wide Web</cTitle>: T1 <Title>When Hashes Met Wedges				: A Distributed Algorithm for Finding High Similarity Vectors</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3052633&Exemplar=1&LAN=DE
				
A1 Sharma, Aneesh
A1 Seshadhri, C.
A1 Goel, Ashish
PB International World Wide Web Conferences Steering Committee
YR 2017
K1 matrix multiplication
K1 nearest neighbor search
K1 similarity search
K1 wedge sampling
K1 Information systems
K1 Information retrieval
K1 Retrieval models and ranking
K1 Similarity measures
K1 Networks
K1 Network types
K1 Overlay and other logical network structures
K1 Social media networks
K1 Computing methodologies
K1 Distributed computing methodologies
K1 Distributed algorithms
K1 MapReduce algorithms
K1 Theory of computation
K1 Design and analysis of algorithms
K1 Streaming, sublinear and near linear time algorithms
K1 Nearest neighbor algorithms
K1 Online social networks
SP 431
OP 440
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3038912.3052633
DO https://dl.acm.org/doi/10.1145/3038912.3052633
SF ELIB - SuUB Bremen

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