Ontosophie: A Semi-Automatic System for Ontology Population from Text
This event took place on Monday 06 December 2004 at 12:30
David Celjuska Technical University Kosice, Slovakia
In this talk I will describe Ontosophie, a system for semi-automatic population of ontologies with instances from unstructured text. Extraction rules are generated from annotated text using supervise learning techniques. These rules are then applied to new articles to populate the ontology. Hence, the system classifies stories and populates a hand-crafted ontology with new instances. It is based on three components: Marmot, a natural language processor; Crystal, a dictionary induction tool; and Badger, an information extraction tool.
In the talk I will address the major challenges and introduce confidence values that we implemented in the system to enhance its performance. Different methods of confidence computation will be given and their results compared on a text corpus consisting of KMi news articles.
Finally, the presentation will be followed with a brief demonstration of Ontosophie.
The talk is being hosted by Dr. Maria Vargas-Vera from KMi.
Download PowerPoint Presentation (133Kb ZIP file)
This event took place on Monday 06 December 2004 at 12:30
David Celjuska Technical University Kosice, Slovakia
In this talk I will describe Ontosophie, a system for semi-automatic population of ontologies with instances from unstructured text. Extraction rules are generated from annotated text using supervise learning techniques. These rules are then applied to new articles to populate the ontology. Hence, the system classifies stories and populates a hand-crafted ontology with new instances. It is based on three components: Marmot, a natural language processor; Crystal, a dictionary induction tool; and Badger, an information extraction tool.
In the talk I will address the major challenges and introduce confidence values that we implemented in the system to enhance its performance. Different methods of confidence computation will be given and their results compared on a text corpus consisting of KMi news articles.
Finally, the presentation will be followed with a brief demonstration of Ontosophie.
The talk is being hosted by Dr. Maria Vargas-Vera from KMi.
Download PowerPoint Presentation (133Kb ZIP file)
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Our research in the Semantic Web area looks at the potentials of fusing together advances in a range of disciplines, and applying them in a systemic way to simplify the development of intelligent, knowledge-based web services and to facilitate human access and use of knowledge available on the web. For instance, we are exploring ways in which tnatural language interfaces can be used to facilitate access to data distributed over different repositories. We are also developing infrastructures to support rapid development and deployment of semantic web services, which can be used to create web applications on-the-fly. We are also investigating ways in which semantic technology can support learning on the web, through a combination of knowledge representation support, pedagogical theories and intelligent content aggregation mechanisms. Finally, we are also investigating the Semantic Web itself as a domain of analysis and performing large scale empirical studies to uncover data about the concrete epistemologies which can be found on the Semantic Web. This exciting new area of research gives us concrete insights on the different conceptualizations that are present on the Semantic Web by giving us the possibility to discover which are the most common viewpoints, which viewpoints are mutually inconsistent, to what extent different models agree or disagree, etc...
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