PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Hierarchical text categorization using coding matrices
Janez Brank, Dunja Mladenić and Marko Grobelnik
In: SiKDD 2006, 09 Oct 2006, Ljubljana, Slovenia.


We discuss the task of ontology population as a machine learning problem with a large hierarchy of classes. Since many machine learning methods are designed primarily for two-class problems, it is desirable to transform the multiclass classification problem into several two-class problems. Coding matrices are a unifying formalism for describing such transformations. We present an approach for constructing coding matrices in a greedy way, with a focus on achieving good performance with a tractable number of two-class classification models.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:2402
Deposited By:Blaz Fortuna
Deposited On:22 November 2006