Dong Zhou
LLAMA: automatic hypertext generation utilizing language models
Zhou, Dong; Goulding, James; Truran, Mark; Brailsford, Tim
Authors
Abstract
Manual hypertext construction is labour intensive and prone to error. Robust systems capable of automatic hypertext generation (AHG) could be of direct benefit to those individuals responsible for hypertext authoring. In this paper we propose a novel technique for the autonomous creation of hypertext which is dependent upon language models. This work is strongly influenced by those algorithms which process the hyperlinked structure of a corpus in an attempt to find authoritative sources. The algorithm was evaluated by experimental comparison with human hypertext authors, and we found that both approaches produced broadly similar results.
Presentation Conference Type | Conference Paper (unpublished) |
---|---|
Conference Name | Eighteenth ACM Conference on Hypertext and Hypermedia (HT07) |
Acceptance Date | Jan 1, 2007 |
Publication Date | Sep 10, 2007 |
Deposit Date | Oct 4, 2018 |
Peer Reviewed | Peer Reviewed |
Pages | 77-80 |
ISBN | 9781595938206 |
Public URL | https://uwe-repository.worktribe.com/output/1025007 |
Additional Information | Title of Conference or Conference Proceedings : Proceedings of the eighteenth conference on Hypertext and hypermedia (HT07) |
Contract Date | Oct 4, 2018 |
You might also like
The ethical and social implications of personalization technologies for e-learning
(2014)
Journal Article
On the Turing Completeness of the Semantic Web
(2014)
Journal Article
Towards computation of novel ideas from corpora of scientific text
(2015)
Presentation / Conference Contribution
Enhancing reflective learning experiences in museums through interactive installations
(2018)
Journal Article
AnswerPro: Designing to motivate interaction
(-0001)
Presentation / Conference Contribution
Downloadable Citations
About UWE Bristol Research Repository
Administrator e-mail: repository@uwe.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search