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Tech Report kmi-04-15 Abstract


AQUA: A Knowledge-Based Architecture for a Question Answering System
Techreport ID: kmi-04-15
Date: 2004
Author(s): Maria Vargas-Vera, Enrico Motta
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This paper describes AQUA, a question answering system. AQUA combines Natural Language processing (NLP), Ontologies, Logic, and Information Retrieval technologies in a uniform framework. AQUA makes intensive use of an ontology (which encodes knowledge) in several parts of the question answering system. The ontology is used in the refinement of the initial query, the reasoning process (a generalization/specialization process using classes and subclasses from the ontology), and in the novel similarity algorithm. The similarity algorithm is a key feature of AQUA. It is used to find similarities between relations/concepts in the translated query and relations/concepts in the ontological structures. The similarities detected then allow the interchange of concepts or relations in a logic formula corresponding to the user query. In this way, we make the mapping between user's queries and ontological spaces. The AQUA architecture is flexible enough to allow that AQUA can be used as closed-domain and open domain question answering system.
 
KMi Publications 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.