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» Algorithms for Querying by Spatial Structure
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KDD
2005
ACM
162views Data Mining» more  KDD 2005»
16 years 4 months ago
Discovering frequent topological structures from graph datasets
The problem of finding frequent patterns from graph-based datasets is an important one that finds applications in drug discovery, protein structure analysis, XML querying, and soc...
Ruoming Jin, Chao Wang, Dmitrii Polshakov, Sriniva...
155
Voted
SG
2009
Springer
15 years 11 months ago
Feature-Driven Volume Fairing
Abstract. Volume datasets have been a primary representation for scientific visualization with the advent of rendering algorithms such as marching cubes and ray casting. Nonethele...
Shigeo Takahashi, Jun Kobayashi, Issei Fujishiro
BMCBI
2005
80views more  BMCBI 2005»
15 years 4 months ago
Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm
Background: Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently ...
Kevin Dawson, Raymond L. Rodriguez, Wasyl Malyj
ICDE
2005
IEEE
156views Database» more  ICDE 2005»
16 years 5 months ago
Reverse Nearest Neighbors in Large Graphs
A reverse nearest neighbor (RNN) query returns the data objects that have a query point as their nearest neighbor (NN). Although such queries have been studied quite extensively in...
Man Lung Yiu, Dimitris Papadias, Nikos Mamoulis, Y...
SSD
2007
Springer
146views Database» more  SSD 2007»
15 years 10 months ago
Blind Evaluation of Nearest Neighbor Queries Using Space Transformation to Preserve Location Privacy
In this paper we propose a fundamental approach to perform the class of Nearest Neighbor (NN) queries, the core class of queries used in many of the location-based services, withou...
Ali Khoshgozaran, Cyrus Shahabi