The cross-lingual transfer is a promising technique to solve tasks in
le...
As the impact of technology on our lives is increasing, we witness incre...
The work covers the development and explainability of machine learning m...
Automatic term extraction (ATE) is a Natural Language Processing (NLP) t...
Automatic term extraction plays an essential role in domain language
und...
Efficiently identifying keyphrases that represent a given document is a
...
The COVID-19 pandemic has been severely impacting global society since
D...
Keyword extraction is the task of retrieving words that are essential to...
Named entity recognition (NER) is an information extraction technique th...
Increasing amounts of freely available data both in textual and relation...
The COVID-19 pandemic triggered a wave of novel scientific literature th...
The current dominance of deep neural networks in natural language proces...
Ontologies are increasingly used for machine reasoning over the last few...
Keyword extraction is the task of identifying words (or multi-word
expre...
Identification of Fake News plays a prominent role in the ongoing pandem...
The abundance of literature related to the widespread COVID-19 pandemic ...
Neural language models are becoming the prevailing methodology for the t...
With growing amounts of available textual data, development of algorithm...
State of the art natural language processing tools are built on
context-...
We propose a new method that leverages contextual embeddings for the tas...
Research in automatic emotion recognition has seldom addressed the issue...
We present a set of novel neural supervised and unsupervised approaches ...
Modeling relations between languages can offer understanding of language...
Keyword extraction is used for summarizing the content of a document and...
The use of background knowledge remains largely unexploited in many text...