Derrac, Joaquin and Schockaert, Steven  ORCID: https://orcid.org/0000-0002-9256-2881
2014.
Characterising semantic relatedness using interpretable directions in conceptual spaces.
Presented at: 2nd European Conference on Artificial Intelligence (ECAI),
Prague, Czech Republic,
18-22 August 2014.
Published in: Schaub, Torsten, Friedrich, Gerhard and O'Sullivan, Barry eds.
ECAI 2014: 21st European Conference on Artificial Intelligence.
Frontiers in Artificial Intelligence and Applications
, vol.263
Amsterdam:
IOS Press,
pp. 243-248.
10.3233/978-1-61499-419-0-243
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Abstract
Various applications, such as critique-based recommendation systems and analogical classifiers, rely on knowledge of how different entities relate. In this paper, we present a methodology for identifying such semantic relationships, by interpreting them as qualitative spatial relations in a conceptual space. In particular, we use multi-dimensional scaling to induce a conceptual space from a relevant text corpus and then identify directions that correspond to relative properties such as “more violent than” in an entirely unsupervised way. We also show how a variant of FOIL is able to learn natural categories from such qualitative representations, by simulating a fortiori inference, an important pattern of commonsense reasoning.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Publisher: | IOS Press |
| ISBN: | 9781614994183 |
| Funders: | EPSRC |
| Date of First Compliant Deposit: | 30 March 2016 |
| Last Modified: | 27 Oct 2022 10:01 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/68591 |
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