43 citations · 141 across the 21 of their papers we have counts for
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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…
Text classification with word embedding regularization and soft similarity measure
Vít Novotný, Eniafe Festus Ayetiran, Michal Štefánik +1
Since the seminal work of Mikolov et al., word embeddings have become the preferred word representations for many natural language processing tasks. Document similarity measures ex…
MIaS: Math-Aware Retrieval in Digital Mathematical Libraries
Petr Sojka, Michal Růžička, Vít Novotný
Digital mathematical libraries (DMLs) such as arXiv, Numdam, and EuDML contain mainly documents from STEM fields, where mathematical formulae are often more important than text for…
Semantic Vector Encoding and Similarity Search Using Fulltext Search Engines
Jan Rygl, Jan Pomikálek, Radim Řehůřek +3
Vector representations and vector space modeling (VSM) play a central role in modern machine learning. We propose a novel approach to `vector similarity searching' over dense seman…
Combining Text and Formula Queries in Math Information Retrieval: Evaluation of Query Results Merging Strategies
Martin Líška, Petr Sojka, Michal Růžička
Specific to Math Information Retrieval is combining text with mathematical formulae both in documents and in queries. Rigorous evaluation of query expansion and merging strategies…