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AIIA
2005
Springer

A Semantic Kernel to Exploit Linguistic Knowledge

10 years 5 months ago
A Semantic Kernel to Exploit Linguistic Knowledge
Abstract. Improving accuracy in Information Retrieval tasks via semantic information is a complex problem characterized by three main aspects: the document representation model, the similarity estimation metric and the inductive algorithm. In this paper an original kernel function sensitive to external semantic knowledge is defined as a document similarity model. This semantic kernel was tested over a text categorization task, under critical learning conditions (i.e. poor training data). The results of cross-validation experiments suggest that the proposed kernel function can be used as a general model of document similarity for IR tasks.
Roberto Basili, Marco Cammisa, Alessandro Moschitt
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where AIIA
Authors Roberto Basili, Marco Cammisa, Alessandro Moschitti
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