Evaluation of Morphological Embeddings for
Year: 2019
Type: conference-paper
Abstract: This paper evaluates morphology-based embeddings for English and Russian languages. Despite the interest and introduction of several morphology-based word embedding models in the past and acclaimed performance improvements on word similarity and language modeling tasks, in our experiments, we did not observe any stable preference over two of our baseline models - SkipGram and FastText. The performance exhibited by morphological embeddings is the average of the two baselines mentioned above.
DOI: 10.18653/v1/w19-2010
Authors: Vitaly Romanov, Albina Khusainova
Institution: Innopolis University
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4288076191