Makrai Márton: Three-order normalized PMI and other lessons in tensor analysis of verbal selectional preferences. In: Magyar Számítógépes Nyelvészeti Konferencia, (18). pp. 105-120. (2022)
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Abstract
We investigate several questions in transitive verb structure representation by decomposing tensors populated with different subject-verb-object association measures, including a novel generalization of normalized pointwise mutual information to the higher-order (>2) case. Which association measure works the best in modeling verb structures? Should we include occurrences with unfilled arguments in our statistics? We also investigate qualitatively the latent dimensions, and the difference between each noun as a subject versus an object.
Item Type: | Article |
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Heading title: | Szintaxis |
Journal or Publication Title: | Magyar Számítógépes Nyelvészeti Konferencia |
Date: | 2022 |
Volume: | 18 |
ISBN: | 978-963-306-848-9 |
Page Range: | pp. 105-120 |
Language: | English |
Place of Publication: | Szeged |
Event Title: | Magyar számítógépes nyelvészeti konferencia (18.) (2022) (Szeged) |
Related URLs: | http://acta.bibl.u-szeged.hu/75797/ |
Uncontrolled Keywords: | Nyelvészet - számítógép alkalmazása |
Additional Information: | Bibliogr.: p. 116-120. ; ill. ; összefoglalás angol nyelven |
Subjects: | 01. Natural sciences 01. Natural sciences > 01.02. Computer and information sciences 06. Humanities 06. Humanities > 06.02. Languages and Literature |
Date Deposited: | 2022. May. 24. 15:36 |
Last Modified: | 2022. May. 24. 15:36 |
URI: | http://acta.bibl.u-szeged.hu/id/eprint/75868 |
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