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10,592
A fast algorithm for incremental distance calculation
 Proc. IEEE Int. Conf. on Robotics and Automation
, 1991
"... Abstract A simple and efficient algorithm for finding the closest points between two convex polyhedra is described here. Data from numerous experiments tested on a broad set of convex polyhedra on !X3 show that the running time is roughly constant for finding closest points when nearest points are ..."
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Cited by 189 (4 self)
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are approximately known and is linear in total number of vertices if no special initialization is done. This algorithm can be used for collision detection, computation of the distance between two polyhedra in threedimensional space, and other robotics problems. It forms the heart of the motion planning algorithm
Answer Validation by Information Distance Calculation
"... In this paper,an information distance based approach is proposed to perform answer validation for question answering system. To validate an answer candidate, the approach calculates the conditional information distance between the question focus and the candidate under certain condition pattern set. ..."
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In this paper,an information distance based approach is proposed to perform answer validation for question answering system. To validate an answer candidate, the approach calculates the conditional information distance between the question focus and the candidate under certain condition pattern set
An efficient distance calculation method for uncertain objects
 IN: PROCEEDINGS OF 2007 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING (CIDM
, 2007
"... Recently the academic communities have paid more attention to the queries and mining on uncertain data. In the tasks such as clustering or nearestneighbor queries, expected distance is often used as a distance measurement among uncertain data objects. Traditional database systems store uncertain o ..."
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Cited by 4 (1 self)
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objects using their expected (average) location in the data space. Distances can be calculated easily from the expected locations, but it poorly approximates the real expected distance values. Recent research work calculates the expected distance by calculating the weighted average of the pair
Relationship Between Cepheid and TullyFisher Distance Calculations
, 2003
"... A correlation between (1) the difference between the TullyFisher calculated distance and Cepheid calculated distance for a target galaxy and (2) the magnitude and distance of galaxies close to the target galaxy is described. The result is based on a sample of 31 galaxies that have published Cepheid ..."
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A correlation between (1) the difference between the TullyFisher calculated distance and Cepheid calculated distance for a target galaxy and (2) the magnitude and distance of galaxies close to the target galaxy is described. The result is based on a sample of 31 galaxies that have published
Rapid Performance of a Generalized Distance Calculation
"... Abstract The everincreasing size of data sets and the need for realtime processing drives the need for high speed analysis. Since traditional CPUs are designed to execute a small number of sequential process, they are illsuited to keep pace with this growth and exploit the massive parallelism in ..."
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the performance improvement of GPUs in data analysis and clustering, this paper presents an implementation of a general ndimensional distance calculation commonly used in these types of algorithms. Experimental results show up to a 390x speedup using a Tesla C1060 and up to a 538x speedup using a GeForce GTX 480
Semantic similarity based on corpus statistics and lexical taxonomy
 Proc of 10th International Conference on Research in Computational Linguistics, ROCLING’97
, 1997
"... This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better quantifie ..."
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Cited by 873 (0 self)
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This paper presents a new approach for measuring semantic similarity/distance between words and concepts. It combines a lexical taxonomy structure with corpus statistical information so that the semantic distance between nodes in the semantic space constructed by the taxonomy can be better
Multipoint quantitativetrait linkage analysis in general pedigrees
 Am. J. Hum. Genet
, 1998
"... Multipoint linkage analysis of quantitativetrait loci (QTLs) has previously been restricted to sibships and small pedigrees. In this article, we show how variancecomponent linkage methods can be used in pedigrees of arbitrary size and complexity, and we develop a general framework for multipoint i ..."
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Cited by 567 (60 self)
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identitybydescent (IBD) probability calculations. We extend the sibpair multipoint mapping approach of Fulker et al. to general relative pairs. This multipoint IBD method uses the proportion of alleles shared identical by descent at genotyped loci to estimate IBD sharing at arbitrary points along a
Fast and accurate Hausdorff distance calculation between meshes
 In WSCG
, 2005
"... Complex models generated e.g. with a laser range scanner often consist of several thousand or million triangles. For efficient rendering this high number of primitives has to be reduced. An important property of mesh reduction – or simplification – algorithms used for rendering is the control over t ..."
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Cited by 11 (2 self)
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algorithm to measure the Hausdorff distance between two meshes by sampling the meshes only in regions of high distance. In addition to comparing two arbitrary meshes, this algorithm can also be applied to check the Hausdorff error between the simplified and original meshes during simplification. By using
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 ..."
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Cited by 390 (21 self)
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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
Results 1  10
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