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Tech Report kmi-01-08 Abstract


Template-Driven Information Extraction for Populating Ontologies
Techreport ID: kmi-01-08
Date: 2001
Author(s): Maria Vargas-Vera, John Domingue, Yannis Kalfoglou, Enrico Motta and Simon Buckingham-Shum
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We address the integration of information extraction (IE) and ontologies. In particular, using an ontology to aid the IE process, and using the IE results to help populate the ontology. We perform IE by means of domain specific templates and the lightweight use of Natural Languages Processing techniques (NLP). Our main goal is to learn information from text by the use of templates and in this way to alleviate the main bottleneck in creating knowledge-base systems that is ``the extraction of knowledge''. Our domain of study is ``KMi Planet'', a Web-based news server that helps to communicate relevant information between members in our institute [Domingue and Scott, 1999]. The raw input consists of e-mailed stories written by members of the laboratory. The main goals of our system are to classify the story, obtain the relevant objects within the story, deduce the relationships between them, and to populate the ontology. Furthermore, we aim to do this with minimal help from the user.

Publication(s):

Submitted to the IJCAI'01 Workshop on Ontology Learning (OL-2001), Seattle, USA, August 4, 2001.
 
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Social Software is...


Social Software
Social Software can be thought of as "software which extends, or derives added value from, human social behaviour - message boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking."

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.