Text classification with word embedding regularization and soft similarity measure

10 Mar 2020Vít NovotnýEniafe Festus AyetiranMichal ŠtefánikPetr Sojka

Since the seminal work of Mikolov et al., word embeddings have become the preferred word representations for many natural language processing tasks. Document similarity measures extracted from word embeddings, such as the soft cosine measure (SCM) and the Word Mover's Distance (WMD), were reported to achieve state-of-the-art performance on semantic text similarity and text classification... (read more)

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