Automatic Ontology Population from French Classified Advertisements

Tracking #: 2985-4199

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Celine Alec

Responsible editor: 
Aldo Gangemi

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Full Paper
Artificial intelligence has become one of the most studied fields in computer science. It aims at building smart machines capable of performing tasks that typically require human intelligence. One of the challenging tasks consists in understanding texts written in natural language. Semantic Web technologies, in particular ontologies, can be used to help agents representing knowledge from a specific domain and reasoning like a human would do. Ontology population from texts aims to translate textual contents into ontological assertions. This paper deals with an approach of automatic ontology population from French textual descriptions. This approach has been designed to be domain-independent, as long as a domain ontology is provided. It relies on a text-based and a knowledge-based analysis, which are fully explained. Experiments performed on French classified advertisements are discussed and provide encouraging results.
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