Harvesting Relational and Structured Knowledge for Ontology Building in the WPro architecture
Daniele Bagni, Marco Cappella, Marco Pennacchiotti, Maria Teresa Pazienza and Armando Stellato
The 10th Congress of the Italian Association for Artificial Intelligence (AIIA 2007)
Roma, Italy, September 10-13, 2007
Abstract
In this paper we present two algorithms for supporting semiautomatic ontology building. The two algorithms are integrated in WPro, a new architecture for ontology learning from Web documents. The first algorithm automatically extracts ontological entities from tables, by using specific heuristics and WordNet based analysis. The second algorithm harvests semantic relations from unstructured texts using Natural Language Processing techniques. Both algorithms are integrated in the WPro architecture, allowing a friendly interaction with the user for validating and modifying the extracted knowledge, and for uploading it into an existing ontology. Both algorithms show promising performance in the extraction process, and offer a practical means to speed-up the overall ontology building process.