Results 1 to 10 of about 29,938 (141)
Nearest neighbor search on embeddings rapidly identifies distant protein relations [PDF]
Frontiers in Bioinformatics, 2022 Since 1992, all state-of-the-art methods for fast and sensitive identification of evolutionary, structural, and functional relations between proteins (also referred to as “homology detection”) use sequences and sequence-profiles (PSSMs). Protein Language
Konstantin Schütze +6 more
doaj +2 more sources
Approximate Nearest Neighbor Search by Residual Vector Quantization [PDF]
Sensors, 2010 A recently proposed product quantization method is efficient for large scale approximate nearest neighbor search, however, its performance on unstructured vectors is limited.
Cheng Wang, Tao Guan, Yongjian Chen
doaj +2 more sources
Accumulative Quantization for Approximate Nearest Neighbor Search. [PDF]
Comput Intell Neurosci, 2022 To further improve the approximate nearest neighbor (ANN) search performance, an accumulative quantization (AQ) is proposed and applied to effective ANN search. It approximates a vector with the accumulation of several centroids, each of which is selected from a different codebook.
Ai L +6 more
europepmc +4 more sources
Capacity-Limited Failure in Approximate Nearest Neighbor Search on Image Embedding Spaces [PDF]
Journal of ImagingSimilarity search on image embeddings is a common practice for image retrieval in machine learning and pattern recognition systems. Approximate nearest neighbor (ANN) methods enable scalable similarity search on large datasets, often approaching sub ...
Morgan Roy Cooper, Mike Busch
doaj +2 more sources
Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations [PDF]
Bioinformatics and Biology Insights, 2017 The associations between proteins and diseases are crucial information for investigating pathological mechanisms. However, the number of known and reliable protein-disease associations is quite small.
Apichat Suratanee, Kitiporn Plaimas
doaj +2 more sources
Approximate Nearest Neighbor Search Based on Neighbor Graphs with Parameter Adaptation [PDF]
Jisuanji gongcheng, 2022 Approximate Nearest Neighbor Search(ANNS) algorithms based on neighbor graphs typically organize vectors in a database into a neighbor graph structure and obtain the Approximate Nearest Neighbor(ANN) of the query vector by leveraging user-specified ...
GAN Hongnan, ZHANG Kai
doaj +1 more source
Semi-supervised inverted file index approach for approximate nearest neighbor search
Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï, 2023 This paper introduces a novel modification to the Inverted File (IVF) index approach for approximate nearest neighbor search, incorporating supervised learning techniques to enhance the efficacy of intermediate clustering and achieve more balanced ...
Anton Bazdyrev
doaj +1 more source
Secure Cloud-Aided Approximate Nearest Neighbor Search on High-Dimensional Data
IEEE Access, 2023 As one fundamental data-mining problem, ANN (approximate nearest neighbor search) is widely used in many industries including computer vision, information retrieval, and recommendation system.
Jia Liu +7 more
doaj +1 more source
Authenticated Multi-Step Nearest Neighbor Search [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2010 Multi-step processing is commonly used for nearest neighbor (NN) and similarity search in applications involving high-dimensional data and/or costly distance computations. Today, many such applications require a proof of result correctness. In this setting, clients issue NN queries to a server that maintains a database signed by a trusted authority ...
Papadopoulos, S. +4 more
openaire +2 more sources
IEEE Access, 2020 The k-nearest neighbor (kNN) algorithm is a classic supervised machine learning algorithm. It is widely used in cyber-physical-social systems (CPSS) to analyze and mine data.
Wei Zhang +3 more
doaj +1 more source