Journal on Communications ›› 2017, Vol. 38 ›› Issue (Z1): 127-134.doi: 10.11959/j.issn.1000-436x.2017245

• Papers • Previous Articles     Next Articles

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

Xin-pan YUAN1,Can-fei WANG1,Jun LONG2,Cheng-yuan ZHANG2,Jun-feng MAN1   

  1. 1 Key Laboratory of Intelligent Information Perception and Processing Technology,School of Computer Science ,Hunan University of Technology,Zhuzhou 412007 ,China
    2 School of Information Science and Engineering,Central South University,Changsha 410083,China
  • Online:2017-10-01 Published:2018-06-07
  • Supported by:
    The National Natural Science Foundation of China(61402165);The National Natural Science Foundation of China(S1651002);The Key Research and Devel-opment Plan of Hunan Province(2016JC2018);The Graduate Student Innovation Plan of Hunan University of Technology(CX1606)

Abstract:

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.

Key words: distance computation, more fine-grained, iDistance, range query

CLC Number: 

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