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» Evaluating algorithms that learn from data streams
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WWW
2004
ACM
16 years 4 months ago
OntoMiner: bootstrapping ontologies from overlapping domain specific web sites
In this paper, we present automated techniques for bootstrapping and populating specialized domain ontologies by organizing and mining a set of relevant overlapping Web sites prov...
Hasan Davulcu, Srinivas Vadrevu, Saravanakumar Nag...
JUCS
2010
164views more  JUCS 2010»
15 years 2 months ago
On Sustainability of Context-Aware Services Among Heterogeneous Smart Spaces
Abstract: Most of ambient intelligence studies have tried to employ inductive methods (e.g., data mining) to discover useful information and patterns from data streams on sensor ne...
Jason J. Jung
TMI
2010
208views more  TMI 2010»
14 years 10 months ago
Patient-Specific Modeling and Quantification of the Aortic and Mitral Valves From 4-D Cardiac CT and TEE
As decisions in cardiology increasingly rely on non-invasive methods, fast and precise image processing tools have become a crucial component of the analysis workflow. To the best ...
Razvan Ioan Ionasec, Ingmar Voigt, Bogdan Georgesc...
AAAI
2012
13 years 6 months ago
Online Kernel Selection: Algorithms and Evaluations
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
PVLDB
2010
89views more  PVLDB 2010»
15 years 2 months ago
Recognizing Patterns in Streams with Imprecise Timestamps
Large-scale event systems are becoming increasingly popular in a variety of domains. Event pattern evaluation plays a key role in monitoring applications in these domains. Existin...
Haopeng Zhang, Yanlei Diao, Neil Immerman