A genetic algorithm (GA) is utilised to discover known and novel PROSITE-like sequence templates that can be used to classify the sub-cellular location of eukaryotic proteins. Whi...
Machine Learning techniques are successfully applied to establish quantitative relations between chemical structure and biological activity (QSAR), i.e. classify compounds as activ...
In this paper, we study the use of support vector machine in text categorization. Unlike other machine learning techniques, it allows easy incorporation of new documents into an e...
We present some novel machine learning techniques for the identification of subcategorization information for verbs in Czech. We compare three different statistical techniques app...
The problem of automatically filtering out spam e-mail using a classifier based on machine learning methods is of great recent interest. This paper gives an introduction to mach...
Bart Massey, Mick Thomure, Raya Budrevich, Scott L...
Bagging and boosting, two effective machine learning techniques, are applied to natural language parsing. Experiments using these techniques with a trainable statistical parser ar...
Documentimageunderstandingdenotesthe recognition of semanticallyrelevant componentsin the layout extracted froma documentimage.This recognitionprocessis based on somevisual models...
Floriana Esposito, Donato Malerba, Francesca A. Li...
Large scale multi-agent systems (MASs) in unpredictable environments must use machine learning techniques to perform their goals and improve the performance of the system. This pap...
In this paper, we describe the research using machine learning techniques to build a comma checker to be integrated in a grammar checker for Basque. After several experiments, and...
In recent years, we have witnessed the success of autonomous agents applying machine learning techniques across a wide range of applications. However, agents applying the same mac...