141 citations · 299 across the 9 of their papers we have counts for
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cs.CL2019
Wasserstein distances for evaluating cross-lingual embeddings
Georgios Balikas, Ioannis Partalas
Word embeddings are high dimensional vector representations of words that capture their semantic similarity in the vector space. There exist several algorithms for learning such em…
cs.IR2019★ 7 cited
Hotel2vec: Learning Attribute-Aware Hotel Embeddings with Self-Supervision
Ali Sadeghian, Shervin Minaee, Ioannis Partalas +3
We propose a neural network architecture for learning vector representations of hotels. Unlike previous works, which typically only use user click information for learning item emb…