期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2021
卷号：2021
页码：126-136
语种：English
出版社：ACL Anthology
摘要：The vast majority of the existing approaches for taxonomy enrichment apply word embeddings as they have proven to accumulate contexts (in a broad sense) extracted from texts which are sufficient for attaching orphan words to the taxonomy. On the other hand, apart from being large lexical and semantic resources, taxonomies are graph structures. Combining word embeddings with graph structure of taxonomy could be of use for predicting taxonomic relations. In this paper we compare several approaches for attaching new words to the existing taxonomy which are based on the graph representations with the one that relies on fastText embeddings. We test all methods on Russian and English datasets, but they could be also applied to other wordnets and languages.
