https://www.ronpub.com/ojwt/OJWT_2018v5i1n04_Cruz.html Channel of the paper: Christophe Cruz, Cyril Nguyen Van and Laurent Gautier: Word Embeddings for Wine Recommender Systems Using Vocabularies of Experts and Consumers, Open Journal of Web Technologies (OJWT), 5 (1), pages 23-30, URN: urn:nbn:de:101:1-2018093019302313586232, 2018, Special Issue: Proceedings of the International Workshop on Web Data Processing & Reasoning (WDPAR 2018) in conjunction with the 41st German Conference on Artificial Intelligence (KI) in Berlin, Germany. en-us https://www.ronpub.com/ojwt/OJWT_2018v5i1n04_Cruz.html http://nbn-resolving.de/urn:nbn:de:101:1-2018093019302313586232 This vision paper proposes an approach to use the most advanced word embeddings techniques to bridge the gap between the discourses of experts and non-experts and more specifically the terminologies used by the twocommunities. Word embeddings makes it possible to find equivalent terms between experts and non-experts, byapproach the similarity between words or by revealing hidden semantic relations. Thus, these controlledvocabularies with these new semantic enrichments are exploited in a hybrid recommendation system incorporating content-based ontology and keyword-based ontology to obtain relevant wines recommendations regardless of the level of expertise of the end user. The major aim is to find a non-expert vocabulary from semantic rules to enrich the knowledge of the ontology and improve the indexing of the items (i.e. wine) and the recommendation process.