Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Martinc, Matej"'
Autor:
Montariol, Syrielle, Martinc, Matej, Pelicon, Andraž, Pollak, Senja, Koloski, Boshko, Lončarski, Igor, Valentinčič, Aljoša
For assessing various performance indicators of companies, the focus is shifting from strictly financial (quantitative) publicly disclosed information to qualitative (textual) information. This textual data can provide valuable weak signals, for exam
Externí odkaz:
http://arxiv.org/abs/2404.05281
In this paper, we focus on the detection of semantic changes in Slovene, a less resourced Slavic language with two million speakers. Detecting and tracking semantic changes provides insights into the evolution of the language caused by changes in soc
Externí odkaz:
http://arxiv.org/abs/2402.16596
Automatic term extraction (ATE) is a Natural Language Processing (NLP) task that eases the effort of manually identifying terms from domain-specific corpora by providing a list of candidate terms. As units of knowledge in a specific field of expertis
Externí odkaz:
http://arxiv.org/abs/2301.06767
Publikováno v:
International Conference on Asian Digital Libraries (ICADL 2022)
Automatic term extraction plays an essential role in domain language understanding and several natural language processing downstream tasks. In this paper, we propose a comparative study on the predictive power of Transformers-based pretrained langua
Externí odkaz:
http://arxiv.org/abs/2212.05696
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 categorised into groups of adjectives exhibiting formal or semantic sim
Externí odkaz:
http://arxiv.org/abs/2203.16885
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-most level, approaches are divided into ones that require training -
Externí odkaz:
http://arxiv.org/abs/2202.06650
Keyword extraction is the task of identifying words (or multi-word expressions) that best describe a given document and serve in news portals to link articles of similar topics. In this work we develop and evaluate our methods on four novel data sets
Externí odkaz:
http://arxiv.org/abs/2102.00472
Autor:
Martinc, Matej, Škrlj, Blaž, Pirkmajer, Sergej, Lavrač, Nada, Cestnik, Bojan, Marzidovšek, Martin, Pollak, Senja
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 tens of thousands of scientific publications with the aim to enrich ex
Externí odkaz:
http://arxiv.org/abs/2007.15681
Publikováno v:
Martinc, M., \v{S}krlj, B., & Pollak, S. (2021). TNT-KID: Transformer-based neural tagger for keyword identification. Natural Language Engineering, 1-40. doi:10.1017/S1351324921000127
With growing amounts of available textual data, development of algorithms capable of automatic analysis, categorization and summarization of these data has become a necessity. In this research we present a novel algorithm for keyword identification,
Externí odkaz:
http://arxiv.org/abs/2003.09166
Publikováno v:
WWW 20 Companion Proceedings of the Web Conference 2020 (April 2020) p. 343-349
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 evolution in textual data, even in short periods of time. In this paper w
Externí odkaz:
http://arxiv.org/abs/2001.06629