Tongxin xuebao (Oct 2017)

FGBC-iDistance:fine-grained bit-code filter based high-dimensional index

  • Xin-pan YUAN,
  • Can-fei WANG,
  • Jun LONG,
  • Cheng-yuan ZHANG,
  • Jun-feng MAN

Journal volume & issue
Vol. 38
pp. 127 – 134

Abstract

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In the high-dimensional vector retrieval,distance computation is a very time-consuming operation,the current research trend is to reduce the distance computation using divide and conquer algorithm.iDistance algorithm divides the vector space into subspace of clustering by pivot,BC-iDistance algorithm divides the subspace into 2 partitions in each dimension.A more fine-grained partition algorithm and index structure was proposed,each part corresponded with a unique FGBC code (fine-grained bit code),which realized the candidate sets filtered more precisely.The distance computation times of FGBC-iDistance can be reduced to 1 2 2d of iDistance.The distance computation frequency comparison:FGBC-iDistance≤BC-iDistance≤iDistance.The experiment results show that when the scope radius of the range query is 0.08,FGBC-iDistance distance computation times is about 20,000,which is far less than other algorithms,the running time is also reduced.

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