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» A General Framework for Graph Sparsification
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142
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HICSS
2002
IEEE
212views Biometrics» more  HICSS 2002»
15 years 8 months ago
Connectivity-Based k-Hop Clustering in Wireless Networks
Abstract. In this paper we describe several new clustering algorithms for nodes in a mobile ad hoc network. The main contribution is to generalize the cluster definition and forma...
Geng Chen, Fabian Garcia Nocetti, Julio Solano-Gon...
129
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JODS
2007
102views Data Mining» more  JODS 2007»
15 years 3 months ago
Default Clustering with Conceptual Structures
This paper describes a theoretical framework for inducing knowledge from incomplete data sets. The general framework can be used with any formalism based on a lattice structure. It...
Julien Velcin, Jean-Gabriel Ganascia
160
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ICCV
2011
IEEE
14 years 3 months ago
Robust Topological Features for Deformation Invariant Image Matching
Local photometric descriptors are a crucial low level component of numerous computer vision algorithms. In practice, these descriptors are constructed to be invariant to a class o...
Edgar Lobaton, Ramanarayan Vasudevan, Ron Alterovi...
142
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EDBT
2009
ACM
208views Database» more  EDBT 2009»
15 years 10 months ago
Flexible and efficient querying and ranking on hyperlinked data sources
There has been an explosion of hyperlinked data in many domains, e.g., the biological Web. Expressive query languages and effective ranking techniques are required to convert this...
Ramakrishna Varadarajan, Vagelis Hristidis, Louiqa...
144
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CIKM
2009
Springer
15 years 10 months ago
SPIDER: a system for scalable, parallel / distributed evaluation of large-scale RDF data
RDF is a data model for representing labeled directed graphs, and it is used as an important building block of semantic web. Due to its flexibility and applicability, RDF has bee...
Hyunsik Choi, Jihoon Son, YongHyun Cho, Min Kyoung...