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  • 标题:Online Generation of Locality Sensitive Hash Signatures
  • 本地全文:下载
  • 作者:Benjamin Van Durme ; Ashwin Lall
  • 期刊名称:Conference on European Chapter of the Association for Computational Linguistics (EACL)
  • 出版年度:2010
  • 卷号:2010
  • 出版社:ACL Anthology
  • 摘要:Motivated by the recent interest in streaming algorithms for processing large text collections, we revisit the work of Ravichandran et al. (2005) on using the Locality Sensitive Hash (LSH) method of Charikar (2002) to enable fast, approximate comparisons of vector cosine similarity. For the common case of feature updates being additive over a data stream, we show that LSH signatures can be maintained online, without additional approximation error, and with lower memory requirements than when using the standard offline technique.
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