Efficient similarity search in scientific databases with feature signatures

Efficient similarity search in scientific databases with feature signatures
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使用特征签名在科学数据库中进行高效相似性搜索

DOI:
10.1145/2791347.2791384
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发表时间:
2015
期刊:
Proceedings of the 27th International Conference on Scientific and Statistical Database Management
影响因子:
--
通讯作者:
T. Seidl
T. Seidl
中科院分区:
--
文献类型:
--
作者:
M. S. Uysal;C. Beecks;J. Schmücking;T. Seidl

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最近科学数据的快速增长需要高效的相似性搜索技术,方便的对象表示模型是至关重要的。表示高度灵活的对象特征表示的特征签名越来越受到关注,为此开发了相应的效率改进技术。在本文中,我们专注于高效的查询处理与著名的地球移动者的距离(EMD)的特征签名数据库,并提出有效的近似技术,成功地适用于高维特征签名通过降维,保证完整性和没有错误的解雇内的过滤和细化架构。对真实的世界数据进行的严格实验表明,所提出的技术大大减少了EMD计算的数量和效率,从而显着减少了查询处理时间。
The recent rapid growth of scientific data necessitates efficient similarity search techniques for which convenient object representation models are of vital importance. Feature signatures denoting highly flexible object feature representations have increasingly gained attention for which corresponding efficiency improvement techniques are developed. In this paper, we focus on efficient query processing with the well-known Earth Mover's Distance (EMD) on databases of feature signatures, and propose efficient approximation techniques successfully applicable to high-dimensional feature signatures via dimensionality reduction, guaranteeing both completeness and no false-dismissal within a filter-and-refine architecture. Rigorous experiments on real world data indicate a considerable reduction in the number of EMD computations and high efficiency of the proposed techniques which significantly reduce the query processing time.
基于相似性的多媒体检索的自适应距离函数
DOI: --
发表时间: 2006
期刊: Datenbank-Spektrum
影响因子: --
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影响因子: --
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