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

• Datum: 2020
• Hauptverfasser: Palagin, O.V., Velychko, V.Yu., Malakhov, K.S., Shchurov, O.S.
• Format: Artikel
• Sprache: English
• Veröffentlicht: PROBLEMS IN PROGRAMMING 2020
• Schlagworte: distributional semantics; vector space model; word embedding; term extraction; term embedding; ontology; ontology engineering; UDC 004.91: 004.912
• Online Zugang: https://pp.isofts.kiev.ua/index.php/ojs1/article/view/426
• Назва журналу: Problems in programming

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...