k-nearest-neighbor search
Secure K-Nearest Neighbor Search By Keywords
... Information Mining has wide applications in numerous territories, for example, saving money, prescription, experimental examination and among government organizations. Grouping is one of the regularly utilized ...
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Survey on Classification and Prediction Approaches in Traffic Flow
... K-nearest neighbor has nonparametric, small error ratio and good error ...of k-nearest neighbor prediction model is to build a representative historical database with large ...of ...
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An Initialization Method for the K means Algorithm using RNN and Coupling Degree
... Since K-means is widely used for general clustering, its performance is a critical ...for K-means clustering is ...reverse nearest neighbor (RNN) search and coupling ...Reverse ...
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Analysis on Fast Nearest Neighbor Search with Keywords
... is nearest neighbor search. Nearest neighbor search (NNS), also identified as closeness search, parallel search is an optimization problem for finding closest ...
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Nearest Neighbor Search with Anytime Clustering Method
... actual k nearest neighbors is ...the K nearest neighbors on large-scale ...the nearest data point of a given query point with increasing ...and nearest- neighbor ...The ...
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Pruned fuzzy K nearest neighbor classifier for beat classification
... Fuzzy K-nearest neighbor (PFKNN) classifier is proposed for beat classifica- ...efficient nearest neighbor search called ATRIA [18] has been ...
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Nearest Neighbor Search with Keywords Using Spatial Inverted Index
... database search and Information Retrieval ...top- k spatial keyword search algorithm, which is inspired by the work of Hjaltason and Samet , exploits this information to locate the top query results ...
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#9 pdf
... the k-nearest neighbors of the object to be ...ity search [16], have been developed for efficient computation of k-nearest neighbor distance that make use of the structure in the ...
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Retrieving Datasets with Nearest Neighbor Search using Spatial Queries
... The strength of IR-tree is ability to perform document searching a document, computational document relevance, and the document ranking in an integrated fashion. At this point, an IR-tree index both the documents of ...
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FAST NEAREST NEIGHBOR SEARCH WITH KEYWORDS
... databases, k nearest neighbor (kNN) and range queries are fundamental query ...for nearest neighbor queries are designed in the context of spatial ...
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Hubless Nearest Neighbor Search for Bilingual Lexicon Induction
... HNN, k for CSLS) should be set as the ones that achieve the best accuracy on the seeding ...and k = 10) used in the MUSE repository, since us- ing them, we can reproduce the results reported in (Conneau et ...
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Keyword Search For Nearest Neighbor Using IR 2 - TREE
... • The IR2-Tree is proposed as an efficient indexing Structure to store spatial and textual information for a set of objects. Efficient algorithms are also presented to maintain the IR2- Tree, that is, insert and delete ...
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RECURSIVE ANTIHUB2 OUTLIER DETECTION IN HIGH DIMENSIONAL DATA
... its k nearest neighbours[2]. A quick and efficient way to identify k nearest neighbors of each point by linearizing the search space through the Hilbert space filling curve is ...kth ...
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A Deterministic K means Algorithm based on Nearest Neighbor Search
... using nearest neighbor search for computing suitable initial clusters centroids instead of random ones, then apply k-means procedure to refine the ...
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k-Expected Nearest Neighbor Search over Gaussian Objects
... distance-based nearest neighbor search, which finds closest objects to a given query point, has extensive applications in various ...extend nearest neighbor search over ...
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SProt: sphere-based protein structure similarity algorithm
... Last of the structure-based methods presented in this overview is 3D-BLAST[14]. This method derives struc- tural alphabet from the - a plot. The structures repre- sented as strings over this alphabet are accessed using ...
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Fast Nearest Neighbor Search with Keywords Using IR2-Tree
... usual search engine indexing algorithms. A goal of a search engine presentation is optimize the speed of the ...1.1.2 Nearest neighbor search (NNS) ...
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Generalized Mean Distance-based k Nearest Centroid Neighbor Classifier
... Non-parametric classifiers provide simple and effective strategies in pattern classification. Especially, the conventional k nearest neighbor (kNN) (Stevens et al., 1967) has been widely used in the ...
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A multi-armed bandit approach for exploring partially observed networks
... choose k-nearest neighbor (k-NN) regression to estimate the expected reward of ...2018)’s k-armed KNN-UCB algorithm to the structured ...
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Spatio-Temporal Query Processing on Weighted Timestamp Data Environment
... Jestes et al. [12] study aggregate top-k queries on temporal data with a piecewise linear representation. The goal is to find the top-k objects with the highest aggregation scores in a given time interval. ...
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