Tech Reports
Tech Report kmi-04-08 Abstract
Indexing Student Essays Paragraphs Using LSA Over an Integrated Ontological Space
Techreport ID: kmi-04-08
Date: 2004
Author(s): Gaston G Burek, Maria Vargas-Vera, Emanuela Moreale
A full understanding of text is out of reach of current human language technology. However, a shallow Natural Language Processing (NLP) approach can be used to provide automated help in the evaluation of essays. The main idea of this paper is that Latent Semantic Indexing (LSA) can be used in conjunction with ontologies and First order Logic (FOL) to locate segments relevant to a question in a student essay. Our test bed, in a first instance, is a set of ontologies such the AKT reference ontology (describing academic life), Newspaper and a Koala ontology (concerning koalas' habitat).
Publication(s):
This paper will be published in the workshop (eLearning for Computational Linguistics and Computational Linguistics for eLearning International Workshop in Association with COLING 2004) proceedings within The 20th International Conference on Computational Linguistics, Geneva, August 28th, 2004.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
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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.
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