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2012 IEEE 24th International Conference on Tools with Artificial Intelligence (2008)
Nov. 3, 2008 to Nov. 5, 2008
ISSN: 1082-3409
ISBN: 978-0-7695-3440-4
pp: 118-125
Information extraction is of paramount importance in several real world applications in the areas of business intelligence, competitive and military intelligence. Although several sophisticated and indeed complex approaches were proposed, they are still limited in many aspects. In this paper the novel ontology-based system named XONTO, that allows the semantic extraction of information from PDF unstructured documents, is presented. The XONTO system is founded on the idea of self-describing ontologies in which objects and classes can be equipped by a set of rules named descriptors. These rules represent patterns that allow to automatically recognize and extract ontology objects contained in PDF documents also when information is arranged in tabular form. This way a self-describing ontology expresses the semantic of the information to extract and the rules that, in turn, populate itself. In the paper XONTO system behaviors and structure are sketched by means of a running example.
Information Extraction, PDF format, Knowledge representation and reasoning, attribute grammars, ontology

M. Ruffolo and E. Oro, "XONTO: An Ontology-Based System for Semantic Information Extraction from PDF Documents," 2008 20th IEEE International Conference on Tools with Artificial Intelligence(ICTAI), vol. 01, no. , pp. 118-125, 2008.
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