Atwell, ES, Arshad, J, Lai, CM et al. (4 more authors) (2007) Which English dominates the world wide web, British or American? In: Proceedings of CL'2007 Corpus Linguistics Conference. CL'2007 Corpus Linguistics Conference, 27-30 Jul 2007, University of Lancaster. UCREL, Lancaster University
Abstract
This paper reports the results of an experiment to combine research and teaching in Corpus Linguistics, using an AI-inspired intelligent agent architecture, but casting students as the intelligent agents (Atwell 2007). Computing students studying Computational Modelling and Technologies for Knowledge Management were given the data-mining coursework task of harvesting and analysing a Data Warehouse from WWW, using WWW-BootCat web-as-corpus technology (Baroni et al 2006). Each student/agent collected English-language web-pages from a specific national top-level domain, and the analysis task involved comparing their national web-as-corpus with given “gold standard” samples from UK and US domains, to assess whether national WWW English terminology/ontology was closer to UK or US English. Results from 93 countries worldwide were collated to give an overview answer to the question: Which English dominates the World Wide Web, British or American?
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Atwell, ES, Arshad, J, Lai, CM, Nim, L, Rezapour Ashregi, N, Wang, J and Washtell, J (c) 2007, University of Leeds. Reproduced with permission from the copyright holders. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence & Biological Systems (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 07 Jan 2015 10:53 |
Last Modified: | 19 Dec 2022 13:29 |
Published Version: | http://ucrel.lancs.ac.uk/publications/CL2007/paper... |
Status: | Published |
Publisher: | UCREL, Lancaster University |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:82245 |