42 citations · 42 across the 2 of their papers we have counts for
7 papers
A bilingual approach to specialised adjectives through word embeddings in the karstology domain
Larisa Grčić Simeunović, Matej Martinc, Špela Vintar
We present an experiment in extracting adjectives which express a specific semantic relation using word embeddings. The results of the experiment are then thoroughly analysed and c…
Out of Thin Air: Is Zero-Shot Cross-Lingual Keyword Detection Better Than Unsupervised?
Boshko Koloski, Senja Pollak, Blaž Škrlj +1
Keyword extraction is the task of retrieving words that are essential to the content of a given document. Researchers proposed various approaches to tackle this problem. At the top…
COVID-19 therapy target discovery with context-aware literature mining
Matej Martinc, Blaž Škrlj, Sergej Pirkmajer +4
The abundance of literature related to the widespread COVID-19 pandemic is beyond manual inspection of a single expert. Development of systems, capable of automatically processing…
Capturing Evolution in Word Usage: Just Add More Clusters?
Matej Martinc, Syrielle Montariol, Elaine Zosa +1
The way the words are used evolves through time, mirroring cultural or technological evolution of society. Semantic change detection is the task of detecting and analysing word evo…
Leveraging Contextual Embeddings for Detecting Diachronic Semantic Shift
Matej Martinc, Petra Kralj Novak, Senja Pollak
We propose a new method that leverages contextual embeddings for the task of diachronic semantic shift detection by generating time specific word representations from BERT embeddin…
Supervised and Unsupervised Neural Approaches to Text Readability
Matej Martinc, Senja Pollak, Marko Robnik-Šikonja
We present a set of novel neural supervised and unsupervised approaches for determining the readability of documents. In the unsupervised setting, we leverage neural language model…