Abstract Context. In the current information era, the problem of analyzing large volumes of unlabeled textual data and its further grouping with respect to the semantic similarity between texts is emerging. This raises the need for robust text analysis algorithms, namely, clustering and extraction of key data from texts. Despite recent progress in the field of natural language processing, new neural methods lack interpretability when used for unsupervised tasks, whereas traditional distributed semantics and word counting techniques tend to disregard contextual information.
Dergi Türü : Uluslararası
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