Results 11  20
of
5,702
Multicast Operation of the Adhoc OnDemand Distance Vector Routing Protocol
, 1999
"... An adhoc network is the cooperative engagement of a collection of (typically wireless) mobile nodes without the required intervention of any centralized access point or existing infrastructure. To provide optimal communication ability, a routing protocol for such a dynamic selfstarting network mu ..."
Abstract

Cited by 446 (3 self)
 Add to MetaCart
An adhoc network is the cooperative engagement of a collection of (typically wireless) mobile nodes without the required intervention of any centralized access point or existing infrastructure. To provide optimal communication ability, a routing protocol for such a dynamic selfstarting network
Simple fast algorithms for the editing distance between trees and related problems
 SIAM J. COMPUT
, 1989
"... Ordered labeled trees are trees in which the lefttoright order among siblings is. significant. The distance between two ordered trees is considered to be the weighted number of edit operations (insert, delete, and modify) to transform one tree to another. The problem of approximate tree matching i ..."
Abstract

Cited by 405 (12 self)
 Add to MetaCart
Ordered labeled trees are trees in which the lefttoright order among siblings is. significant. The distance between two ordered trees is considered to be the weighted number of edit operations (insert, delete, and modify) to transform one tree to another. The problem of approximate tree matching
Distance Browsing in Spatial Databases
, 1999
"... Two different techniques of browsing through a collection of spatial objects stored in an Rtree spatial data structure on the basis of their distances from an arbitrary spatial query object are compared. The conventional approach is one that makes use of a knearest neighbor algorithm where k is kn ..."
Abstract

Cited by 390 (21 self)
 Add to MetaCart
Two different techniques of browsing through a collection of spatial objects stored in an Rtree spatial data structure on the basis of their distances from an arbitrary spatial query object are compared. The conventional approach is one that makes use of a knearest neighbor algorithm where k
An Efficient kMeans Clustering Algorithm: Analysis and Implementation
, 2000
"... Kmeans clustering is a very popular clustering technique, which is used in numerous applications. Given a set of n data points in R d and an integer k, the problem is to determine a set of k points R d , called centers, so as to minimize the mean squared distance from each data point to its ..."
Abstract

Cited by 417 (4 self)
 Add to MetaCart
Kmeans clustering is a very popular clustering technique, which is used in numerous applications. Given a set of n data points in R d and an integer k, the problem is to determine a set of k points R d , called centers, so as to minimize the mean squared distance from each data point to its
Polynomial time approximation schemes for Euclidean traveling salesman and other geometric problems
 Journal of the ACM
, 1998
"... Abstract. We present a polynomial time approximation scheme for Euclidean TSP in fixed dimensions. For every fixed c Ͼ 1 and given any n nodes in 2 , a randomized version of the scheme finds a (1 ϩ 1/c)approximation to the optimum traveling salesman tour in O(n(log n) O(c) ) time. When the nodes ..."
Abstract

Cited by 397 (2 self)
 Add to MetaCart
to Christofides) achieves a 3/2approximation in polynomial time. We also give similar approximation schemes for some other NPhard Euclidean problems: Minimum Steiner Tree, kTSP, and kMST. (The running times of the algorithm for kTSP and kMST involve an additional multiplicative factor k.) The previous best
Blobworld: A System for RegionBased Image Indexing and Retrieval
 In Third International Conference on Visual Information Systems
, 1999
"... . Blobworld is a system for image retrieval based on finding coherent image regions which roughly correspond to objects. Each image is automatically segmented into regions ("blobs") with associated color and texture descriptors. Querying is based on the attributes of one or two regions of ..."
Abstract

Cited by 375 (4 self)
 Add to MetaCart
of interest, rather than a description of the entire image. In order to make largescale retrieval feasible, we index the blob descriptions using a tree. Because indexing in the highdimensional feature space is computationally prohibitive, we use a lowerrank approximation to the highdimensional distance
ApplicationLevel Multicast Using ContentAddressable Networks
, 2001
"... Most currently proposed solutions to applicationlevel multicast organize the group members into an applicationlevel mesh over which a DistanceVector routing protocol, or a similar algorithm, is used to construct sourcerooted distribution trees. The use of a global routing protocol limits the s ..."
Abstract

Cited by 372 (8 self)
 Add to MetaCart
Most currently proposed solutions to applicationlevel multicast organize the group members into an applicationlevel mesh over which a DistanceVector routing protocol, or a similar algorithm, is used to construct sourcerooted distribution trees. The use of a global routing protocol limits
Approximate distance oracles
, 2004
"... Let G = (V, E) be an undirected weighted graph with V  = n and E  = m. Let k ≥ 1 be an integer. We show that G = (V, E) can be preprocessed in O(kmn 1/k) expected time, constructing a data structure of size O(kn 1+1/k), such that any subsequent distance query can be answered, approximately, in ..."
Abstract

Cited by 273 (9 self)
 Add to MetaCart
algorithms are extremely simple and easy to implement efficiently. They also provide faster constructions of sparse spanners of weighted graphs, and improved tree covers and distance labelings of weighted or unweighted graphs.
Shape quantization and recognition with randomized trees
 NEURAL COMPUTATION
, 1997
"... We explore a new approach to shape recognition based on a virtually infinite family of binary features ("queries") of the image data, designed to accommodate prior information about shape invariance and regularity. Each query corresponds to a spatial arrangement ofseveral local topographic ..."
Abstract

Cited by 263 (18 self)
 Add to MetaCart
topographic codes ("tags") which are in themselves too primitive and common to be informative about shape. All the discriminating power derives from relative angles and distances among the tags. The important attributes of the queries are (i) a natural partial ordering corresponding to increasing
Clustering by compression
 IEEE Transactions on Information Theory
, 2005
"... Abstract—We present a new method for clustering based on compression. The method does not use subjectspecific features or background knowledge, and works as follows: First, we determine a parameterfree, universal, similarity distance, the normalized compression distance or NCD, computed from the l ..."
Abstract

Cited by 297 (25 self)
 Add to MetaCart
Abstract—We present a new method for clustering based on compression. The method does not use subjectspecific features or background knowledge, and works as follows: First, we determine a parameterfree, universal, similarity distance, the normalized compression distance or NCD, computed from
Results 11  20
of
5,702