22 citations · 35 across the 11 of their papers we have counts for
6 papers · 2 filters
Studying Taxonomy Enrichment on Diachronic WordNet Versions
Irina Nikishina, Alexander Panchenko, Varvara Logacheva +1
Ontologies, taxonomies, and thesauri are used in many NLP tasks. However, most studies are focused on the creation of these lexical resources rather than the maintenance of the exi…
Improving Results on Russian Sentiment Datasets
Anton Golubev, Natalia Loukachevitch
In this study, we test standard neural network architectures (CNN, LSTM, BiLSTM) and recently appeared BERT architectures on previous Russian sentiment evaluation datasets. We comp…
Attention-Based Neural Networks for Sentiment Attitude Extraction using Distant Supervision
Nicolay Rusnachenko, Natalia Loukachevitch
In the sentiment attitude extraction task, the aim is to identify <<attitudes>> -- sentiment relations between entities mentioned in text. In this paper, we provide a study on atte…
Studying Attention Models in Sentiment Attitude Extraction Task
Nicolay Rusnachenko, Natalia Loukachevitch
In the sentiment attitude extraction task, the aim is to identify <<attitudes>> -- sentiment relations between entities mentioned in text. In this paper, we provide a study on atte…
Sentiment Frames for Attitude Extraction in Russian
Natalia Loukachevitch, Nicolay Rusnachenko
Texts can convey several types of inter-related information concerning opinions and attitudes. Such information includes the author's attitude towards mentioned entities, attitudes…
RUSSE'2020: Findings of the First Taxonomy Enrichment Task for the Russian language
Irina Nikishina, Varvara Logacheva, Alexander Panchenko +1
This paper describes the results of the first shared task on taxonomy enrichment for the Russian language. The participants were asked to extend an existing taxonomy with previousl…