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» Efficient kernel feature extraction for massive data sets
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ALGORITHMICA
2002
103views more  ALGORITHMICA 2002»
13 years 7 months ago
Efficient Bulk Operations on Dynamic R-Trees
In recent years there has been an upsurge of interest in spatial databases. A major issue is how to manipulate efficiently massive amounts of spatial data stored on disk in multidi...
Lars Arge, Klaus Hinrichs, Jan Vahrenhold, Jeffrey...
ICST
2010
IEEE
13 years 5 months ago
Automated Test Data Generation on the Analyses of Feature Models: A Metamorphic Testing Approach
A Feature Model (FM) is a compact representation of all the products of a software product line. The automated extraction of information from FMs is a thriving research topic invo...
Sergio Segura, Robert M. Hierons, David Benavides,...
EMMCVPR
2009
Springer
14 years 2 months ago
Clustering-Based Construction of Hidden Markov Models for Generative Kernels
Generative kernels represent theoretically grounded tools able to increase the capabilities of generative classification through a discriminative setting. Fisher Kernel is the fi...
Manuele Bicego, Marco Cristani, Vittorio Murino, E...
DASFAA
2005
IEEE
191views Database» more  DASFAA 2005»
14 years 1 months ago
An Efficient Approach to Extracting Approximate Repeating Patterns in Music Databases
Pattern extraction from music strings is an important problem. The patterns extracted from music strings can be used as features for music retrieval or analysis. Previous works on ...
Ning-Han Liu, Yi-Hung Wu, Arbee L. P. Chen
SMC
2007
IEEE
133views Control Systems» more  SMC 2007»
14 years 2 months ago
Text classification using multi-word features
—We carried out a series of experiments on text classification using multi-word features. An automated method was proposed to extract the multi-words from text data set and two d...
Wen Zhang, Taketoshi Yoshida, Xijin Tang