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Approximate Nearest Neighbor Search Using Enhanced Accumulative Quantization

Electronics (Switzerland), 2022
Approximate nearest neighbor (ANN) search is fundamental for fast content-based image retrieval. While vector quantization is one key to performing an effective ANN search, in order to further improve ANN search accuracy, we propose an enhanced ...
Liefu Ai, Xiaoxiao Wang, Xin Zheng
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Approximate nearest neighbor searching in multimedia databases

Proceedings 17th International Conference on Data Engineering, 2002
Develops a general framework for approximate nearest-neighbor queries. We categorize the current approaches for nearest-neighbor query processing based on either their ability to reduce the data set that needs to be examined, or their ability to reduce the representation size of each data object.
Hakan Ferhatosmanoglu, Ertem Tuncel, Divyakant Agrawal, Amr El Abbadi   +3 more
openaire   +1 more source

ConANN: Conformal Approximate Nearest Neighbor Search [PDF]

Proceedings of the VLDB Endowment
Approximate Nearest Neighbor (ANN) search is widely used in applications such as recommendation systems, search engines, and natural language processing. Indexing techniques like the Inverted File (IVF) offer efficiency at the cost of accuracy, yet lack formal mechanisms to quantify or control approximation error.
Sonia Horchidan, Fabian Zeiher, Henrik Boström, Paris Carbone   +3 more
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Expected-Case Complexity of Approximate Nearest Neighbor Searching

SIAM Journal on Computing, 2003
Summary: Most research in algorithms for geometric query problems has focused on their worst-case performance. However, when information on the query distribution is available, the alternative paradigm of designing and analyzing algorithms from the perspective of expected-case performance appears more attractive.
Arya, Sunil, Fu, HYA
openaire   +4 more sources

Order preserving hashing for approximate nearest neighbor search

Proceedings of the 21st ACM international conference on Multimedia, 2013
In this paper, we propose a novel method to learn similarity-preserving hash functions for approximate nearest neighbor (NN) search. The key idea is to learn hash functions by maximizing the alignment between the similarity orders computed from the original space and the ones in the hamming space.
Jianfeng Wang, Jingdong Wang 0001, Nenghai Yu, Shipeng Li 0001   +3 more
openaire   +1 more source

New Directions in Approximate Nearest-Neighbor Searching

2019
Approximate nearest-neighbor searching is an important retrieval problem with numerous applications in science and engineering. This problem has been the subject of many research papers spanning decades of work. Recently, a number of dramatic improvements and extensions have been discovered.
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Product tree quantization for approximate nearest neighbor search

2015 IEEE International Conference on Image Processing (ICIP), 2015
The product quantization (PQ) performance degrades on read-world data due to the severity of dependence between feature groups. Meanwhile, tree structured vector quantization (TSVQ) often supply lower distortion than other structured vector quantizers; yet it is prohibitive to learning compact codes like PQ does considering its codebook storage.
Jiangbo Yuan, Xiuwen Liu 0001
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Optimized Product Quantization for Approximate Nearest Neighbor Search

2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013
Product quantization is an effective vector quantization approach to compactly encode high-dimensional vectors for fast approximate nearest neighbor (ANN) search. The essence of product quantization is to decompose the original high-dimensional space into the Cartesian product of a finite number of low-dimensional subspaces that are then quantized ...
Tiezheng Ge, Kaiming He, Qifa Ke, Jian Sun 0001   +3 more
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Supporting subseries nearest neighbor search via approximation

Proceedings of the ninth international conference on Information and knowledge management, 2000
Searc hingfor nearest neigh b orsin a large set of time series is an importan tdata mining task. This paper studies the following type of time series nearest neighbor queries: Given a query series and a starting time, among all the subseries (of a collection of data series) that have the same length as the query series and start at the given time, nd ...
Changzhou Wang, Xiaoyang Sean Wang
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A strong lower bound for approximate nearest neighbor searching

Information Processing Letters, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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