Vadim Isakov’s scientific contributions

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Publications (1)


RST Discourse Parser for Russian: An Experimental Study of Deep Learning Models
  • Chapter

April 2021

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72 Reads

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3 Citations

Lecture Notes in Computer Science

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This work presents the first fully-fledged discourse parser for Russian based on the Rhetorical Structure Theory of Mann and Thompson (1988). For the segmentation, discourse tree construction, and discourse relation classification we employ deep learning models. With the help of multiple word embedding techniques, the new state of the art for discourse segmentation of Russian texts is achieved. We found that the neural classifiers using contextual word representations outperform previously proposed feature-based models for discourse relation classification. By ensembling both methods, we are able to further improve the performance of the discourse relation classification achieving the new state of the art for Russian.

Citations (1)


... Due to the availability of the large annotated discourse corpora for many languages, especially English, discourse parsers [19,21,17] provide reliable and correct DT for the text. Manually annotated Ru-RSTreebank corpus [26] has been recently introduced which resulted in the creation of discourse parser for Russian [9]. The availability of state-of-the-art discourse parsers for different languages makes the discourse-based models universal, so they could be applied to different texts without modifications. ...

Reference:

Building medical ontologies relying on communicative discourse trees
RST Discourse Parser for Russian: An Experimental Study of Deep Learning Models
  • Citing Chapter
  • April 2021

Lecture Notes in Computer Science