An Adaptive Subspace Similarity Search Approach

In recent years,such database fields as multimedia information retrieval,similarity join and time series matching,where similarity search has attracted much attention.Existing researches mostly compute nearest neighbor to solve problems about search target set,such as kNN and kNNJ,by metric distance...

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Main Authors: Jianxin Ren, Huahui Chen
Format: Article
Language:zho
Published: Beijing Xintong Media Co., Ltd 2015-07-01
Series:Dianxin kexue
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Online Access:http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2015190/
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author Jianxin Ren
Huahui Chen
author_facet Jianxin Ren
Huahui Chen
author_sort Jianxin Ren
collection DOAJ
description In recent years,such database fields as multimedia information retrieval,similarity join and time series matching,where similarity search has attracted much attention.Existing researches mostly compute nearest neighbor to solve problems about search target set,such as kNN and kNNJ,by metric distance functions in the Euclidean space.But some studies showed that high dissimilarity dimensions had got great effect on the accuracy of answer and flexibility and robustness still were lacked in corresponding solutions.Thus centralized dynamic subspace or partial dimensions similarity search problem and algorithms were proposed at first.Furthermore,with the emerge of very large dataset,centralized algorithms can,t extend very well.Finally,the distributed ones under hadoop framework were proposed.Experiments prove that distributed algorithms outperform centralized ones in the performance without accuracy loss.
format Article
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institution Kabale University
issn 1000-0801
language zho
publishDate 2015-07-01
publisher Beijing Xintong Media Co., Ltd
record_format Article
series Dianxin kexue
spelling doaj-art-8d5ffc1be88e4ad9aed5fa6409e06f522025-01-15T03:17:00ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012015-07-0131637459614691An Adaptive Subspace Similarity Search ApproachJianxin RenHuahui ChenIn recent years,such database fields as multimedia information retrieval,similarity join and time series matching,where similarity search has attracted much attention.Existing researches mostly compute nearest neighbor to solve problems about search target set,such as kNN and kNNJ,by metric distance functions in the Euclidean space.But some studies showed that high dissimilarity dimensions had got great effect on the accuracy of answer and flexibility and robustness still were lacked in corresponding solutions.Thus centralized dynamic subspace or partial dimensions similarity search problem and algorithms were proposed at first.Furthermore,with the emerge of very large dataset,centralized algorithms can,t extend very well.Finally,the distributed ones under hadoop framework were proposed.Experiments prove that distributed algorithms outperform centralized ones in the performance without accuracy loss.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2015190/adaptive subspacesimilarity searchnon-metric distance methodMapReduce distributed computing framework
spellingShingle Jianxin Ren
Huahui Chen
An Adaptive Subspace Similarity Search Approach
Dianxin kexue
adaptive subspace
similarity search
non-metric distance method
MapReduce distributed computing framework
title An Adaptive Subspace Similarity Search Approach
title_full An Adaptive Subspace Similarity Search Approach
title_fullStr An Adaptive Subspace Similarity Search Approach
title_full_unstemmed An Adaptive Subspace Similarity Search Approach
title_short An Adaptive Subspace Similarity Search Approach
title_sort adaptive subspace similarity search approach
topic adaptive subspace
similarity search
non-metric distance method
MapReduce distributed computing framework
url http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2015190/
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AT huahuichen anadaptivesubspacesimilaritysearchapproach
AT jianxinren adaptivesubspacesimilaritysearchapproach
AT huahuichen adaptivesubspacesimilaritysearchapproach