[PDF] Top 20 A Nearest Neighbor Data Structure for Graphics Hardware
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A Nearest Neighbor Data Structure for Graphics Hardware
... the data structures in the two cited papers [2, 18] are advanced forms of metric trees, with search algorithms that guide queries through a deep tree in a highly data-dependent and complex ...multiple ... See full document
6
OPRCP: approximate nearest neighbor binary search algorithm for hybrid data over WMSN blockchain
... index structure, for a single type of data, people performed well with approximate similarity search by constructing feature vector ...image data, there are two index structures ...index ... See full document
14
Analysis on Fast Nearest Neighbor Search with Keywords
... Nearest neighbor search (NNS), also known as closest point search, similarity ...points. Nearest neighbor search which returns the nearest neighbor of a query point in a set of ... See full document
5
FAST NEAREST NEIGHBOR SEARCH WITH KEYWORDS
... a structure called MHR-tree to answer spatial approximate-keyword ...index structure is to augment a tree-based spatial index with approximate string indexes such as a gram-based inverted index or a ... See full document
11
Quick Search of the Nearest Neighbor with Words
... multidimensional data. The best method to date for nearest neighbor search with keywords is due to Felipe et ...a structure called the IR2 -tree, which has the strengths of both R-trees and ... See full document
5
Nearest neighbor imputation algorithms: a critical evaluation
... Background: Nearest neighbor (NN) imputation algorithms are efficient methods to fill in missing data where each missing value on some records is replaced by a value obtained from related cases in ... See full document
12
K-Nearest Neighbor Classification Mechanism of Secure Encrypted Relational Data
... encoded structure, and also the information mining errands to the ...encoded structure, existing protection safeguarding grouping systems are not ... See full document
8
Bayesian inference network for molecular similarity searching using 2D fingerprints and multiple reference structures
... Second, the data fusion and nearest neighbor methods conducts an individual similarity search for each active reference structure, and then "fuses" the resulting similarity value[r] ... See full document
13
1. Spatial data mining for finding nearest neighbor and outlier detection
... Spatial data mining is a process to extract interesting patterns related to ...molecular structure, or a human ...noisy data or highly valuable ...of data mining algorithm may be degraded ... See full document
7
Data Recovery on Encrypted Databases With k-Nearest Neighbor Query Leakage
... Another setting that could be considered is the one where the adversary observes a subset of the identifiers. Specifically, when the attacker sees the identifiers for a range of consecutive Voronoi segments, the ... See full document
22
Survey of Efficient and Fast Nearest Neighbor Search For Spatial Query on Multidimensional Data
... reverse nearest neighbor query, hybrid indexing structure bR*-tree, efficient method to answer top-k spatial keyword query, computing the relevance between the documents of an object and a query, ... See full document
10
Pseudometrics for Nearest Neighbor Classification of Time Series Data
... good structure to perform nearest neighbor pattern ...-nearest neighbor when the sample size grows ...faster nearest neighbor search ... See full document
24
Nearest Neighbor Search with Anytime Clustering Method
... the data are divided to some partitions and the nearest neighbor or distance is obtained over these ...the nearest neighbor search and cannot give the exact value of ...index ... See full document
6
K NEAREST NEIGHBOR LOGISTIC REGRESSION FOR STABLE AND CONSISTENT DATA DELIVERY IN WSN
... organizational structure-less wireless ...maximum data loss and delay during data ...K Nearest Neighbour- based Logistic Regression (KNN-LR) framework is ...during data transmission. As ... See full document
14
Nearest Neighbor Voting in High Dimensional Data: Learning from Past Occurrences
... to nearest-neighbor ...the neighbor occurrences carry more information than others, by the virtue of being less frequent ...k-Nearest Neighbor (HIKNN), which introduces the k-occurrence ... See full document
22
Online Full Text
... the data piling ...eliminating data piling and the associated overfitting ...real data examples results suggest that, in the presence of irrelevant or redundant variables, the sparse LDA method can ... See full document
6
Sparse Linear Discriminant Analysis with Applications to High Dimensional Low Sample Size Data
... the data piling problem. As an illustration of the data piling problem, Figure 1 provides views of two simulated data sets, one of which serves as a training data set, shown in the first row, ... See full document
13
K-Nearest Neighbor Classification over Semantically Secure Encrypted Relational Data
... relational data has been studied extensively, and many theoretical and practical solutions to query processing have been proposed under various ...their data as well as the data management tasks to ... See full document
7
An Ensemble of Classifiers using Dynamic Method on Ambiguous Data
... Abstract- The aim of proposed work is to analyze the Instance Selection Algorithm first. There are Weighted Instance Selection algorithms are available such as wDROP3 (weighted Decremental Reduction Optimization ... See full document
8
Züfle, Andreas (2013): Similarity search and mining in uncertain spatial and spatio-temporal databases. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik
... uncertain data, including the U-Topk and U-kRanks queries, and argued for a more robust definition of ranking, namely the expected rank for each tuple (or ... See full document
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