Distributional semantic modeling: a revised technique to train term/word vector space models applying the ontology-related approach

• Veröffentlicht in: Проблеми програмування
• Datum: 2020
• Hauptverfasser: Palagin, O.V., Velychko, V.Yu., Malakhov, K.S., Shchurov, O.S.
• Format: Artikel
• Sprache: Englisch
• Veröffentlicht: Інститут програмних систем НАН України 2020
• Schlagworte: Методи машинного навчання
• Online Zugang: https://nasplib.isofts.kiev.ua/handle/123456789/180480
• 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.

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...