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Machine Learning-Based Risk Prediction for Coronary Heart Disease Complicated by Hyperhomocysteinemia: Retrospective Study.

JMIR Med Inform
Du MY, Lyu MK, Liu HL, Li YZ, Yan HF, Li XH.   +5 more
europepmc   +1 more source

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Hit-Directed Nearest-Neighbor Searching

Journal of Medicinal Chemistry, 2004
This work describes a practical strategy used at Pharmacia for identifying compounds for follow-up screening following an initial HTS campaign against targets where no 3-D structural information is available and preliminary SAR models do not exist. The approach explicitly takes into account different representations of chemistry space and identifies ...
Veerabahu, Shanmugasundaram, Gerald M, Maggiora, Michael S, Lajiness   +2 more
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Nearest-Neighbor Searching Under Uncertainty I

Discrete & Computational Geometry, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Pankaj K. Agarwal, Alon Efrat, Swaminathan Sankararaman, Wuzhou Zhang   +3 more
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Succinct nearest neighbor search

Proceedings of the Fourth International Conference on SImilarity Search and APplications, 2011
In this paper we present a novel technique for nearest neighbor searching dubbed neighborhood approximation. The central idea is to divide the database into compact regions represented by a single object, called the reference. To search for nearest neighbors a set of candidate references is first obtained and later enriched with the database objects ...
Eric Sadit Tellez, Edgar Chavez, Gonzalo Navarro   +2 more
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Nearest neighbor search

SIGSPATIAL Special, 2010
Nearest Neighbor Search is a task to design a pair of algorithms for the following scenario. A dataset S of n objects is given and preprocessing algorithm is applied. Then a query object q is presented and search algorithm is used to find the nearest to q
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Multiple k nearest neighbor search

World Wide Web, 2016
The problem of kNN (k Nearest Neighbor) queries has received considerable attention in the database and information retrieval communities. Given a dataset D and a kNN query q, the k nearest neighbor algorithm finds the closest k data points to q. The applications of kNN queries are board, not only in spatio-temporal databases but also in many areas ...
Yu-Chi Chung, I-Fang Su, Chiang Lee, Pei-Chi Liu   +3 more
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Asymmetric Mapping Quantization for Nearest Neighbor Search

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
Nearest neighbor search is a fundamental problem in computer vision and machine learning. The straightforward solution, linear scan, is both computationally and memory intensive in large scale high-dimensional cases, hence is not preferable in practice.
Weixiang Hong, Xueyan Tang, Jingjing Meng, Junsong Yuan   +3 more
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High dimensional nearest neighbor searching

Information Systems, 2006
As databases increasingly integrate different types ot Information SUCh as time-series, multimedia and scientific data, it becomes necessary to support efficient retrieval of multi-dimensional data. Both the dimensionality and the amount of data that needs to be processed are increasing rapidly. As a result of the scale and high dimensional nature, the
Hakan Ferhatosmanoglu, Ertem Tuncel, Divyakant Agrawal, Amr El Abbadi   +3 more
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Hash Bit Selection for Nearest Neighbor Search

IEEE Transactions on Image Processing, 2017
To overcome the barrier of storage and computation when dealing with gigantic-scale data sets, compact hashing has been studied extensively to approximate the nearest neighbor search. Despite the recent advances, critical design issues remain open in how to select the right features, hashing algorithms, and/or parameter settings.
Xianglong Liu, Junfeng He, Shih-Fu Chang
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