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» Granular clustering: a granular signature of data
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ISSTA
2009
ACM
14 years 4 months ago
Identifying bug signatures using discriminative graph mining
Bug localization has attracted a lot of attention recently. Most existing methods focus on pinpointing a single statement or function call which is very likely to contain bugs. Al...
Hong Cheng, David Lo, Yang Zhou, Xiaoyin Wang, Xif...
ACSW
2004
13 years 11 months ago
Cost-Efficient Mining Techniques for Data Streams
A data stream is a continuous and high-speed flow of data items. High speed refers to the phenomenon that the data rate is high relative to the computational power. The increasing...
Mohamed Medhat Gaber, Shonali Krishnaswamy, Arkady...
CCGRID
2007
IEEE
14 years 4 months ago
Dynamic Malleability in Iterative MPI Applications
Malleability enables a parallel application’s execution system to split or merge processes modifying granularity. While process migration is widely used to adapt applications to...
Kaoutar El Maghraoui, Travis J. Desell, Boleslaw K...
ACL
2006
13 years 11 months ago
Discriminating Image Senses by Clustering with Multimodal Features
We discuss Image Sense Discrimination (ISD), and apply a method based on spectral clustering, using multimodal features from the image and text of the embedding web page. We evalu...
Nicolas Loeff, Cecilia Ovesdotter Alm, David A. Fo...
JCP
2006
111views more  JCP 2006»
13 years 9 months ago
Mining Developing Trends of Dynamic Spatiotemporal Data Streams
This paper1 presents an efficient modeling technique for data streams in a dynamic spatiotemporal environment and its suitability for mining developing trends. The streaming data a...
Yu Meng, Margaret H. Dunham