| Issue |
ITM Web Conf.
Volume 8, 2016
International Conference on Big Data and its Applications (ICBDA 2016)
|
|
|---|---|---|
| Article Number | 01006 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/itmconf/20160801006 | |
| Published online | 22 November 2016 | |
Learning Word Subsumption Projections for the Russian Language
1 Krasovskii Institute of Mathematics and Mechanics, 620990 Yekaterinburg, Russia
2 Ural Federal University, 620002 Yekaterinburg, Russia
3 Technische Universität Darmstadt, Computer Science Department, Language Technology Group, 64289 Darmstadt, Germany
* Corresponding author: dau@imm.uran.ru
The semantic relations of hypernymy and hyponymy are widely used in various natural language processing tasks for modelling the subsumptions in common sense reasoning. Since the popularisation of the distributional semantics, a significant attention is paid to applying word embeddings for inducing the relations between words. In this paper, we show our preliminary results on adopting the projection learning technique for computing hypernyms from hyponyms using word embeddings. We also conduct a series of experiments on the Russian language and release the open source software for learning hyponym-hypernym projections using both CPUs and GPUs, implemented with the TensorFlow machine learning framework.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.