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» BAG: a graph theoretic sequence clustering algorithm
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ER
2004
Springer
103views Database» more  ER 2004»
14 years 1 months ago
Modeling Default Induction with Conceptual Structures
Our goal is to model the way people induce knowledge from rare and sparse data. This paper describes a theoretical framework for inducing knowledge from these incomplete data descr...
Julien Velcin, Jean-Gabriel Ganascia
RECOMB
2004
Springer
14 years 8 months ago
A random graph approach to NMR sequential assignment
Nuclear magnetic resonance (NMR) spectroscopy allows scientists to study protein structure, dynamics and interactions in solution. A necessary first step for such applications is ...
Chris Bailey-Kellogg, Sheetal Chainraj, Gopal Pand...
WG
2010
Springer
13 years 6 months ago
Parameterized Complexity of the Arc-Preserving Subsequence Problem
Abstract. We study the Arc-Preserving Subsequence (APS) problem with unlimited annotations. Given two arc-annotated sequences P and T, this problem asks if it is possible to delete...
Dániel Marx, Ildikó Schlotter
ACMSE
2006
ACM
14 years 1 months ago
Discovering communities in complex networks
We propose an efficient and novel approach for discovering communities in real-world random networks. Communities are formed by subsets of nodes in a graph, which are closely rela...
Hemant Balakrishnan, Narsingh Deo
KAIS
2011
129views more  KAIS 2011»
13 years 2 months ago
Counting triangles in real-world networks using projections
Triangle counting is an important problem in graph mining. Two frequently used metrics in complex network analysis which require the count of triangles are the clustering coefficie...
Charalampos E. Tsourakakis