SOTAVerified

WordNet Embeddings

2018-07-01WS 2018Code Available0· sign in to hype

Chakaveh Saedi, Ant{\'o}nio Branco, Jo{\~a}o Ant{\'o}nio Rodrigues, Jo{\~a}o Silva

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Abstract

Semantic networks and semantic spaces have been two prominent approaches to represent lexical semantics. While a unified account of the lexical meaning relies on one being able to convert between these representations, in both directions, the conversion direction from semantic networks into semantic spaces started to attract more attention recently. In this paper we present a methodology for this conversion and assess it with a case study. When it is applied over WordNet, the performance of the resulting embeddings in a mainstream semantic similarity task is very good, substantially superior to the performance of word embeddings based on very large collections of texts like word2vec.

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