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ICPR
2000
IEEE
14 years 10 months ago
Data Condensation in Large Databases by Incremental Learning with Support Vector Machines
An algorithmfor data condensation using support vector machines (SVM's)is presented. The algorithm extracts datapoints lying close to the class boundaries,whichform a much re...
Pabitra Mitra, C. A. Murthy, Sankar K. Pal
ICANN
2003
Springer
14 years 2 months ago
Meta-learning for Fast Incremental Learning
Model based learning systems usually face to a problem of forgetting as a result of the incremental learning of new instances. Normally, the systems have to re-learn past instances...
Takayuki Oohira, Koichiro Yamauchi, Takashi Omori
LREC
2008
89views Education» more  LREC 2008»
13 years 10 months ago
Ontology Learning and Semantic Annotation: a Necessary Symbiosis
Semantic annotation of text requires the dynamic merging of linguistically structured information and a "world model", usually represented as a domain-specific ontology....
Emiliano Giovannetti, Simone Marchi, Simonetta Mon...
ICAIL
2007
ACM
14 years 1 months ago
NLP-based Ontology Learning from Legal Texts. A Case Study
The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts in the environmental d...
Alessandro Lenci, Simonetta Montemagni, Vito Pirre...
KBS
2002
106views more  KBS 2002»
13 years 9 months ago
Hybrid decision tree
In this paper, a hybrid learning approach named HDT is proposed. HDT simulates human reasoning by using symbolic learning to do qualitative analysis and using neural learning to d...
Zhi-Hua Zhou, Zhaoqian Chen