Generators of Words Definitions

Student: Gadetskii Artem

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Final Grade: 10

Year of Graduation: 2018

We investigate recently introduced definition modeling technique that provided the tool for evaluation of different distributed vector representations of words through modeling dictionary definitions of words. In this work, we study the problem of word ambiguities in definition modeling and propose a possible solution by employing latent variable modeling and soft attention mechanisms. In our experiments, we explore different properties of our models and discuss possible important applications beyond definitions’ modeling. Our quantitative and qualitative evaluation and analysis of the model shows that taking into account words’ ambiguity and polysemy leads to performance improvement.

Full text (added May 21, 2018)

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