KMi Seminars
Learning Ontologies by Processing Natural Language Text
This event took place on Wednesday 03 November 2004 at 12:30

Dileep Damle KMi, The Open University

Ontology construction is a costly and slow process requiring ontological engineering skills as well as domain expertise. The semantic web will be greatly facilitated if domain ontologies could be built quickly and cheaply without human expertise of either kind.

One approach to automatic ontology creation is to utilize existing knowledge resources such as database schema. These can be very useful, but are rare and natural language text is more likely to be available for many domains. But complete, unambiguous and accurate interpretation of natural language texts by computers is currently a very major challenge This work is concerned with extracting ontological elements such as concepts, their properties and inter-relationships from natural language corpora in order to grow an ontology for the domain in a semi-automatic way. The hypothesis is that it is not necessary to fully, and unambiguously interpret all sentences in text, but inferences drawn from parts of sentences may be sufficient for the purpose if enough text is available.

The presentation will cover some early results in two of the main areas of this research.

1. Identification of the domain relevant terms in the corpus
2. Some early examples of semantic extractors

 
KMi Seminars Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

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.