Abstract
This work addresses a logical approach to text categorization inside a framework aimed at full automatic paper document processing. The logic representation of sentences required by the adopted learning algorithm is obtained by detecting structure in raw text trough a parser. A preliminary experimentation proved that the logic approach is able to capture the semantics underlying some kind of sentences, even if the assessment of the efficiency of such a method, as well as a comparison with other related approaches, has still to be carried out.
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Ferilli, S., Fanizzi, N., Semeraro, G. (2001). Learning Logic Models for Automated Text Categorization. In: Esposito, F. (eds) AI*IA 2001: Advances in Artificial Intelligence. AI*IA 2001. Lecture Notes in Computer Science(), vol 2175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45411-X_10
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DOI: https://doi.org/10.1007/3-540-45411-X_10
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