<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bonaventura Coppola</style></author><author><style face="normal" font="default" size="100%">Aldo Gangemi</style></author><author><style face="normal" font="default" size="100%">Alfio Massimiliano Gliozzo</style></author><author><style face="normal" font="default" size="100%">Davide Picca</style></author><author><style face="normal" font="default" size="100%">Valentina Presutti</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Frame Detection over the Semantic Web</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 6th European Semantic Web Conference</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Research in ontology learning from text has been mainly focused on entity recognition, taxonomy induction and relation extraction. In this work we approach a more challenging research issue, consisting in detecting semantic frames from texts, and using them to encode web ontologies. We exploit a new generation frame detection system, which is able to identify FrameNet frames and their argument boundaries from text parsing. In addition, we enrich frames with the results provided by a super-sense tagger, which extracts and classiﬁes concepts and named entities from texts according to WordNet super-senses. The enrichment results include argument restrictions for the elements of a frame, and domain specializations, based on domain lexical unit detection for the target of a frame. The results are encoded according to the Lexical MetaModel, which allows a complete translation of lexical resources, keeps trace of the learning metadata, and enables custom transformations of enriched frames into modular ontology components, known as content ontology design patterns.</style></abstract></record></records></xml>