2024 COLING COLING 2024

Interaction of Semantics and Morphology in Russian Word Vectors

Abstract

AbstractIn this paper we explore how morphological information can be extracted from fastText embeddings for Russian nouns. We investigate the negative effects of syncretism and propose ways of modifying the vectors that can help to find better representations for morphological functions and thus for out of vocabulary words. In particular, we look at the effect of analysing shift vectors instead of original vectors, discuss various possibilities of finding base forms to create shift vectors, and show that using only the high frequency data is beneficial when looking for structure with respect to the morphosyntactic functions in the embeddings.

๐ŸŒ‰ Interdisciplinary Bridge โ€” Machine Learning and Natural Language Processing
๐Ÿ Cross-Pollinator โ€” Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio