(3) In recurrent neural networks (RNNs), the subsymbolic units are trained to predict the next word, given all preceding words in the sentences.
no code implementations • • Varvara Logacheva, Denis Teslenko, Artem Shelmanov, Steffen Remus, Dmitry Ustalov, Andrey Kutuzov, Ekaterina Artemova, Chris Biemann, Simone Paolo Ponzetto, Alexander Panchenko
We use this method to induce a collection of sense inventories for 158 languages on the basis of the original pre-trained fastText word embeddings by Grave et al. (2018), enabling WSD in these languages.
Since vectors of the same word type can vary depending on the respective context, they implicitly provide a model for word sense disambiguation (WSD).
Capsule networks have been shown to demonstrate good performance on structured data in the area of visual inference.
Particularly for dynamic systems, where topics are not predefined but formulated as a search query, we believe a more informative approach is to perform user studies for directly comparing different methods in the same view.
In this paper, we describe the concept of entity-centric information access for the biomedical domain.