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)
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Multimedia and Information Systems is...
We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
Visit the MMIS website
List all Multimedia and Information Systems Projects
Check out these Hot Multimedia and Information Systems Technologies:
List all Multimedia and Information Systems Technologies
