kLog is a framework for kernel-based learning that has already proven success- ful in solving a number of relational tasks in natural language processing. In this pa- per, we present kLogNLP, a natural lan- guage processing module for kLog. This module enriches kLog with NLP-specific preprocessors, enabling the use of exist- ing libraries and toolkits within an elegant and powerful declarative machine learn- ing framework. The resulting relational model of the domain can be extended by specifying additional relational features in a declarative way using a logic program- ming language. This declarative approach offers a flexible way of experimentation and a way to insert domain knowledge.
kLogNLP: Graph kernel–based relational learning of natural language / Mathias Verbeke; Paolo Frasconi; Kurt De Grave; Fabrizio Costa; Luc De Raedt. - STAMPA. - (2014), pp. 85-90. (Intervento presentato al convegno Annual Meeting of the Association for Computational Lingusitics (ACL) tenutosi a Baltimore).
kLogNLP: Graph kernel–based relational learning of natural language
FRASCONI, PAOLO;
2014
Abstract
kLog is a framework for kernel-based learning that has already proven success- ful in solving a number of relational tasks in natural language processing. In this pa- per, we present kLogNLP, a natural lan- guage processing module for kLog. This module enriches kLog with NLP-specific preprocessors, enabling the use of exist- ing libraries and toolkits within an elegant and powerful declarative machine learn- ing framework. The resulting relational model of the domain can be extended by specifying additional relational features in a declarative way using a logic program- ming language. This declarative approach offers a flexible way of experimentation and a way to insert domain knowledge.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.