Results 1  10
of
1,042
Mtree: An Efficient Access Method for Similarity Search in Metric Spaces
, 1997
"... A new access meth d, called Mtree, is proposed to organize and search large data sets from a generic "metric space", i.e. whE4 object proximity is only defined by a distance function satisfyingth positivity, symmetry, and triangle inequality postulates. We detail algorith[ for insertion o ..."
Abstract

Cited by 652 (38 self)
 Add to MetaCart
of objects and split management, whF h keep th Mtree always balanced  severalheralvFV split alternatives are considered and experimentally evaluated. Algorithd for similarity (range and knearest neigh bors) queries are also described. Results from extensive experimentationwith a prototype system
Indexing Metric Spaces with Mtree
 PROC. QUINTO CONVEGNO NAZIONALE SEBD
, 1997
"... Mtree is a dynamic access method suitable to index generic “metric spaces”, where the function used to compute the distance between any two objects satisfies the positivity, symmetry, and triangle inequality postulates. The Mtree design fulfills typical requirements of multimedia applications, wh ..."
Abstract

Cited by 8 (0 self)
 Add to MetaCart
Mtree is a dynamic access method suitable to index generic “metric spaces”, where the function used to compute the distance between any two objects satisfies the positivity, symmetry, and triangle inequality postulates. The Mtree design fulfills typical requirements of multimedia applications
Processing Mtrees with Parallel Resources
 In Proceedings of the 6th EDBT International Conference
, 1998
"... The problem of the design and implementation of parallel metric tree indexes, called Mtrees, is elaborated. Four different object declustering techniques are proposed and tested in order to get a sufficient evidence needed for specifying the pros and cons of their application. In general, the obtai ..."
Abstract

Cited by 5 (0 self)
 Add to MetaCart
The problem of the design and implementation of parallel metric tree indexes, called Mtrees, is elaborated. Four different object declustering techniques are proposed and tested in order to get a sufficient evidence needed for specifying the pros and cons of their application. In general
Indexing Metric Spaces with Mtree
, 1997
"... Mtree is a dynamic access method suitable to index generic "metric spaces", where the function used to compute the distance between any two objects satisfies the positivity, symmetry, and triangle inequality postulates. The Mtree design fulfills typical requirements of multimedia applica ..."
Abstract
 Add to MetaCart
Mtree is a dynamic access method suitable to index generic "metric spaces", where the function used to compute the distance between any two objects satisfies the positivity, symmetry, and triangle inequality postulates. The Mtree design fulfills typical requirements of multimedia
Pivoting Mtree: A Metric Access Method for Efficient Similarity Search
, 2004
"... In this paper pivoting Mtree (PMtree) is introduced, a metric access method combining Mtree with the pivotbased approach. ..."
Abstract

Cited by 17 (2 self)
 Add to MetaCart
In this paper pivoting Mtree (PMtree) is introduced, a metric access method combining Mtree with the pivotbased approach.
A Querysensitive Cost Model for Similarity Queries with Mtree
 In Proc. of the 10th ADC
, 1999
"... . We intro duc acS4 model for the Mtree acRNH method [Ciac4( et al., 1997]whic h provides estimates of CPU(distanc cis putations) and I/Oc osts for the execDRS( of similarity queries as a funcSL( ofeac h single query. This model is said to bequerysensit , sinc it takes intoacSSL t, by relying on t ..."
Abstract

Cited by 10 (2 self)
 Add to MetaCart
. We intro duc acS4 model for the Mtree acRNH method [Ciac4( et al., 1997]whic h provides estimates of CPU(distanc cis putations) and I/Oc osts for the execDRS( of similarity queries as a funcSL( ofeac h single query. This model is said to bequerysensit , sinc it takes intoacSSL t, by relying
PeertoPeer Similarity Search based on MTree Indexing
"... Abstract. Similarity search in metric spaces has several important applications both in centralized and distributed environments. In centralized applications, such as similaritybased image retrieval, usually a server indexes its data with a stateoftheart centralized metric indexing technique, su ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
, such as the MTree. In this paper, we propose a framework for distributed similarity search, where each participating peer stores its own data autonomously, under the assumption that data is indexed locally by peers using MTrees. In order to support scalability and efficiency of search, we adopt a super
Mtree: An Efficient Access Method for Similarity Search in Metric Spaces
, 1997
"... A new access method, called Mtree, is proposed to organize and search large data sets from a generic "metric space", i.e. where object proximity is only defined by a distance function satisfying the positivity, symmetry, and triangle inequality postulates. We detail algorithms for i ..."
Abstract
 Add to MetaCart
A new access method, called Mtree, is proposed to organize and search large data sets from a generic "metric space", i.e. where object proximity is only defined by a distance function satisfying the positivity, symmetry, and triangle inequality postulates. We detail algorithms
The M²tree: Processing Complex MultiFeature Queries with Just One Index
"... Motivated by the needs for efficient similarity retrieval in multimedia digital libraries, we present basic principles of a new paged and balanced index structure, the M²tree. The M²tree can be applied whenever "complex" range and/or best matches queries over different descriptions (feat ..."
Abstract
 Add to MetaCart
Motivated by the needs for efficient similarity retrieval in multimedia digital libraries, we present basic principles of a new paged and balanced index structure, the M²tree. The M²tree can be applied whenever "complex" range and/or best matches queries over different descriptions
Optimal MultiStep kNearest Neighbor Search
, 1998
"... For an increasing number of modern database applications, efficient support of similarity search becomes an important task. Along with the complexity of the objects such as images, molecules and mechanical parts, also the complexity of the similarity models increases more and more. Whereas algorithm ..."
Abstract

Cited by 199 (23 self)
 Add to MetaCart
For an increasing number of modern database applications, efficient support of similarity search becomes an important task. Along with the complexity of the objects such as images, molecules and mechanical parts, also the complexity of the similarity models increases more and more. Whereas algorithms that are directly based on indexes work well for simple mediumdimensional similarity distance functions, they do not meet the efficiency requirements of complex highdimensional and adaptable distance functions. The use of a multistep query processing strategy is recommended in these cases, and our investigations substantiate that the number of candidates which are produced in the filter step and exactly evaluated in the refinement step is a fundamental efficiency parameter. After revealing the strong performance shortcomings of the stateoftheart algorithm for knearest neighbor search [Korn et al. 1996], we present a novel multistep algorithm which is guaranteed to produce the minim...
Results 1  10
of
1,042