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» Clustering for metric and nonmetric distance measures
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CVPR
2006
IEEE
14 years 1 months ago
Learning Non-Metric Partial Similarity Based on Maximal Margin Criterion
The performance of many computer vision and machine learning algorithms critically depends on the quality of the similarity measure defined over the feature space. Previous works...
Xiaoyang Tan, Songcan Chen, Jun Li, Zhi-Hua Zhou
INFOCOM
2008
IEEE
14 years 1 months ago
Non-Metric Coordinates for Predicting Network Proximity
—We consider the problem of determining the “closest”, or best Internet host to connect to, from a list of candidate servers. Most existing approaches rely on the use of metr...
Peter B. Key, Laurent Massoulié, Dan-Cristi...
ICDE
1999
IEEE
183views Database» more  ICDE 1999»
14 years 8 months ago
ROCK: A Robust Clustering Algorithm for Categorical Attributes
Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
Sudipto Guha, Rajeev Rastogi, Kyuseok Shim
EDBT
2006
ACM
121views Database» more  EDBT 2006»
14 years 7 months ago
On Fast Non-metric Similarity Search by Metric Access Methods
Abstract. The retrieval of objects from a multimedia database employs a measure which defines a similarity score for every pair of objects. The measure should effectively follow th...
Tomás Skopal
TKDE
2008
171views more  TKDE 2008»
13 years 7 months ago
Efficient Similarity Search in Nonmetric Spaces with Local Constant Embedding
Similarity-based search has been a key factor for many applications such as multimedia retrieval, data mining, Web search and retrieval, and so on. There are two important issues r...
Lei Chen 0002, Xiang Lian