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pro vyhledávání: '"Arcan, Mihael"'
Employee well-being is a critical concern in the contemporary workplace, as highlighted by the American Psychological Association's 2021 report, indicating that 71% of employees experience stress or tension. This stress contributes significantly to w
Externí odkaz:
http://arxiv.org/abs/2402.01592
Mental health challenges pose considerable global burdens on individuals and communities. Recent data indicates that more than 20% of adults may encounter at least one mental disorder in their lifetime. On the one hand, the advancements in large lang
Externí odkaz:
http://arxiv.org/abs/2401.04592
Autor:
Suryawanshi, Shardul, Chakravarthi, Bharathi Raja, Arcan, Mihael, Little, Suzanne, Buitelaar, Paul
Research into the classification of Image with Text (IWT) troll memes has recently become popular. Since the online community utilizes the refuge of memes to express themselves, there is an abundance of data in the form of memes. These memes have the
Externí odkaz:
http://arxiv.org/abs/2109.03571
Autor:
Torregrosa, Daniel, Pasricha, Nivranshu, Masoud, Maraim, Chakravarthi, Bharathi Raja, Alonso, Juan, Casas, Noe, Arcan, Mihael
Rule-based machine translation is a machine translation paradigm where linguistic knowledge is encoded by an expert in the form of rules that translate text from source to target language. While this approach grants extensive control over the output
Externí odkaz:
http://arxiv.org/abs/2009.13398
Publikováno v:
SN Computer Science (2021) 2:330
Machine translation is one of the applications of natural language processing which has been explored in different languages. Recently researchers started paying attention towards machine translation for resource-poor languages and closely related la
Externí odkaz:
http://arxiv.org/abs/2008.01391
Princeton WordNet is one of the most important resources for natural language processing, but is only available for English. While it has been translated using the expand approach to many other languages, this is an expensive manual process. Therefor
Externí odkaz:
http://arxiv.org/abs/1903.01411
While neural networks have been used extensively to make substantial progress in the machine translation task, they are known for being heavily dependent on the availability of large amounts of training data. Recent efforts have tried to alleviate th
Externí odkaz:
http://arxiv.org/abs/1902.08816
Autor:
Arcan, Mihael
In this paper we present a question answering system using a neural network to interpret questions learned from the DBpedia repository. We train a sequence-to-sequence neural network model with n-triples extracted from the DBpedia Infobox Properties.
Externí odkaz:
http://arxiv.org/abs/1803.02914
Our work presented in this paper focuses on the translation of terminological expressions represented in semantically structured resources, like ontologies or knowledge graphs. The challenge of translating ontology labels or terminological expression
Externí odkaz:
http://arxiv.org/abs/1709.02184
Autor:
Arcan, Mihael1 (AUTHOR) mihael.arcan@insight-centre.org, Manjunath, Sampritha1 (AUTHOR), Robin, Cécile1 (AUTHOR), Verma, Ghanshyam1 (AUTHOR), Pillai, Devishree1 (AUTHOR), Sarkar, Simon1 (AUTHOR), Dutta, Sourav2 (AUTHOR), Assem, Haytham3 (AUTHOR), McCrae, John P.1 (AUTHOR), Buitelaar, Paul1 (AUTHOR)
Publikováno v:
Information (2078-2489). May2023, Vol. 14 Issue 5, p288. 20p.
