43 citations · 141 across the 21 of their papers we have counts for
6 papers · 1 filter
Towards Math-Aware Automated Classification and Similarity Search of Scientific Publications: Methods of Mathematical Content Representations
Michal Růžička, Petr Sojka
In this paper, we investigate mathematical content representations suitable for the automated classification of and the similarity search in STEM documents using standard machine l…
Regressive Ensemble for Machine Translation Quality Evaluation
Michal Štefánik, Vít Novotný, Petr Sojka
This work introduces a simple regressive ensemble for evaluating machine translation quality based on a set of novel and established metrics. We evaluate the ensemble using a corre…
WebMIaS on Docker: Deploying Math-Aware Search in a Single Line of Code
Dávid Lupták, Vít Novotný, Michal Štefánik +1
Math informational retrieval (MIR) search engines are absent in the wide-spread production use, even though documents in the STEM fields contain many mathematical formulae, which a…
When FastText Pays Attention: Efficient Estimation of Word Representations using Constrained Positional Weighting
Vít Novotný, Michal Štefánik, Eniafe Festus Ayetiran +2
In 2018, Mikolov et al. introduced the positional language model, which has characteristics of attention-based neural machine translation models and which achieved state-of-the-art…
EDS-MEMBED: Multi-sense embeddings based on enhanced distributional semantic structures via a graph walk over word senses
Eniafe Festus Ayetiran, Petr Sojka, Vít Novotný
Several language applications often require word semantics as a core part of their processing pipeline, either as precise meaning inference or semantic similarity. Multi-sense embe…
One Size Does Not Fit All: Finding the Optimal Subword Sizes for FastText Models across Languages
Vít Novotný, Eniafe Festus Ayetiran, Dalibor Bačovský +3
Unsupervised representation learning of words from large multilingual corpora is useful for downstream tasks such as word sense disambiguation, semantic text similarity, and inform…