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Scaling up all pairs similarity search

Published: 08 May 2007 Publication History

Abstract

Given a large collection of sparse vector data in a high dimensional space, we investigate the problem of finding all pairs of vectors whose similarity score (as determined by a function such as cosine distance) is above a given threshold. We propose a simple algorithm based on novel indexing and optimization strategies that solves this problem without relying on approximation methods or extensive parameter tuning. We show the approach efficiently handles a variety of datasets across a wide setting of similarity thresholds, with large speedups over previous state-of-the-art approaches.

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Published In

cover image ACM Conferences
WWW '07: Proceedings of the 16th international conference on World Wide Web
May 2007
1382 pages
ISBN:9781595936547
DOI:10.1145/1242572
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 May 2007

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Author Tags

  1. data mining
  2. similarity join
  3. similarity search

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WWW'07
Sponsor:
WWW'07: 16th International World Wide Web Conference
May 8 - 12, 2007
Alberta, Banff, Canada

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

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  • (2024)Asynchronous Distributed Actor-Based Approach to Jaccard Similarity for Genome ComparisonsISC High Performance 2024 Research Paper Proceedings (39th International Conference)10.23919/ISC.2024.10528922(1-11)Online publication date: May-2024
  • (2024)FUDJ: Flexible User-Defined Distributed Joins2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00320(4194-4207)Online publication date: 13-May-2024
  • (2024)Multi-level semantic enhancement based on self-distillation BERT for Chinese named entity recognitionNeurocomputing10.1016/j.neucom.2024.127637(127637)Online publication date: Apr-2024
  • (2024)LSH SimilarityJoin Pattern in FastFlowInternational Journal of Parallel Programming10.1007/s10766-024-00772-152:3(207-230)Online publication date: 23-May-2024
  • (2024)Open benchmark for filtering techniques in entity resolutionThe VLDB Journal10.1007/s00778-024-00868-733:5(1671-1696)Online publication date: 9-Jul-2024
  • (2023)A Trie Based Set Similarity Query AlgorithmMathematics10.3390/math1101022911:1(229)Online publication date: 2-Jan-2023
  • (2023)Multiset-Trie Data StructureAlgorithms10.3390/a1603017016:3(170)Online publication date: 20-Mar-2023
  • (2023)Automatic item generation for online measurement and evaluation: Turkish literature itemsAutomatic item generation for online measurement and evaluation: Turkish literature itemsInternational Journal of Assessment Tools in Education10.21449/ijate.124929710:2(218-231)Online publication date: 26-Jun-2023
  • (2023)A Two-Level Signature Scheme for Stable Set Similarity JoinsProceedings of the VLDB Endowment10.14778/3611479.361148016:11(2686-2698)Online publication date: 24-Aug-2023
  • (2023)TokenJoinProceedings of the VLDB Endowment10.14778/3574245.357426316:4(790-802)Online publication date: 21-Feb-2023
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