Distributional semantic modeling: a revised technique to train term/word vector space models applying the ontology-related approach
We design a new technique for the distributional semantic modeling with a neural network-based approach to learn distributed term representations (or term embeddings) – term vector space models as a result, inspired by the recent ontology-related approach (using different types of contextual knowled...
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| Datum: | 2020 |
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| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | English |
| Veröffentlicht: |
Інститут програмних систем НАН України
2020
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| Schriftenreihe: | Проблеми програмування |
| Schlagworte: | |
| Online Zugang: | http://dspace.nbuv.gov.ua/handle/123456789/180480 |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Zitieren: | Distributional semantic modeling: a revised technique to train term/word vector space models applying the ontology-related approach / O.V. Palagin, V.Yu Velychko., K.S. Malakhov, O.S. Shchurov // Проблеми програмування. — 2020. — № 2-3. — С. 341-351. — Бібліогр.: 50 назв. — англ. |