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» Learning to Classify Texts Using Positive and Unlabeled Data
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NLE
2008
108views more  NLE 2008»
13 years 7 months ago
Using automatically labelled examples to classify rhetorical relations: an assessment
Being able to identify which rhetorical relations (e.g., contrast or explanation) hold between spans of text is important for many natural language processing applications. Using ...
Caroline Sporleder, Alex Lascarides
KDD
2010
ACM
272views Data Mining» more  KDD 2010»
13 years 11 months ago
Beyond heuristics: learning to classify vulnerabilities and predict exploits
The security demands on modern system administration are enormous and getting worse. Chief among these demands, administrators must monitor the continual ongoing disclosure of sof...
Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, G...
ECML
2001
Springer
14 years 1 days ago
Iterative Double Clustering for Unsupervised and Semi-supervised Learning
We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...
Ran El-Yaniv, Oren Souroujon
NAACL
2003
13 years 9 months ago
Automatic Extraction of Semantic Networks from Text using Leximancer
Leximancer is a software system for performing conceptual analysis of text data in a largely language independent manner. The system is modelled on Content Analysis and provides u...
Andrew E. Smith
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
13 years 11 months ago
Pareto-coevolutionary genetic programming classifier
The conversion and extension of the Incremental ParetoCoevolution Archive algorithm (IPCA) into the domain of Genetic Programming classifier evolution is presented. In order to ac...
Michal Lemczyk, Malcolm I. Heywood