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attr2vec: Jointly Learning Word and Contextual Attribute Embeddings with Factorization Machines
2018
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
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The widespread use of word embeddings is associated with the recent successes of many natural language processing (NLP) systems. ...
The key approach of popular models such as word2vec and GloVe is to learn dense vector representations from the context of words. ...
In this work, we introduce attr2vec, a novel framework for jointly learning embeddings for words and contextual attributes based on factorization machines. ...
doi:10.18653/v1/n18-1042
dblp:conf/naacl/PetroniPNL18
fatcat:pzzpagyksbhtvjsfllevpg6kuq