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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