Home »
Academic Articles & Research Papers
Showing 16 of 16 academic articles
Yongtai Liu, Zhijun Yin, Congning Ni, Chao Yan et al. • Journal of Medical Internet Research
(2023)
BackgroundBy the end of 2022, more than 100 million people were infected with COVID-19 in the United States, and the cumulative death rate in rural areas (383.5/100,000) was much higher than in urban areas (280.1/100,000). As the pandemic s...
DOAJ
Open Access (DOAJ)
DOI: 10.2196/42985
Peratham Wiriyathammabhum, Douglas A. Summers-Stay, Cornelia M. Fermuller, Yiannis Aloimonos • ACM Computing Surveys
(2016)
Integrating computer vision and natural language processing is a novel interdisciplinary field that has received a lot of attention recently. In this survey, we provide a comprehensive introduction of the integration of computer vision and ...
OPENALEX
DOI: https://doi.org/10.1145/3009906
Jonah A. Berger, Grant M. Packard • American Psychologist
(2021)
Language can provide important insights into people, and culture more generally. Further, the digitization of information has made more and more textual data available. But by itself, all that data are just that: data. Realizing its potenti...
OPENALEX
Open Access
DOI: https://doi.org/10.1037/amp0000882
Kai-Wei Chang, Vinod M. Prabhakaran, Vicente Ordóñez • Conference on Empirical Methods in Natural Language Processing (EMNLP)
(2019)
Recent advances in data-driven machine learning techniques (e.g., deep neural networks) have revolutionized many natural language processing applications. These approaches automatically learn how to make decisions based on the statistics an...
OPENALEX
Asefeh Asemi, Rajab Kiani Shahvandy, Mahdi Houshangi • International Journal of Information Management Data Insights
(2026)
Objective: This study conducts a comprehensive empirical evaluation of semantic clustering algorithms to identify the most effective approach for automatically organizing and extracting meaning from textual data. By systematically comparing...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jjimei.2026.100396
Seyedmostafa Sheikhalishahi, Riccardo Miotto, Joel T. Dudley, Alberto Lavelli et al. • JMIR Medical Informatics
(2019)
BACKGROUND: Novel approaches that complement and go beyond evidence-based medicine are required in the domain of chronic diseases, given the growing incidence of such conditions on the worldwide population. A promising avenue is the seconda...
OPENALEX
cc-by
DOI: https://doi.org/10.2196/12239
PMC: 6528438
Julia El Zini, Mariette Awad • ACM Computing Surveys
(2022)
Despite their success, deep networks are used as black-box models with outputs that are not easily explainable during the learning and the prediction phases. This lack of interpretability is significantly limiting the adoption of such model...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3529755
Dheya Mustafa, Safaa M. Khabour, Mousa Al-kfairy, Ahmed Shatnawi • PeerJ Computer Science
(2025)
Companies that deliver food (food delivery services, or FDS) try to use customer feedback to identify aspects where the customer experience could be improved. Consumer feedback on purchasing and receiving goods via online platforms is a cru...
DOAJ
Open Access (DOAJ)
DOI: 10.7717/peerj-cs.2669
Simov Kiril, Osenova Petya • Cybernetics and Information Technologies
(2018)
With the availability of large language data online, cross-linked lexical resources (such as BabelNet, Predicate Matrix and UBY) and semantically annotated corpora (SemCor, OntoNotes, etc.), more and more applications in Natural Language Pr...
DOAJ
Open Access (DOAJ)
DOI: 10.2478/cait-2018-0008
Jawanpuria, Pratik, Balgovind, Arjun, Kunchukuttan, Anoop, Mishra, Bamdev • Transactions of the Association for Computational Linguistics
(2019)
We propose a novel geometric approach for learning bilingual mappings given monolingual embeddings and a bilingual dictionary. Our approach decouples the source-to-target language transformation into (a) language-specific rotations on the o...
DOAJ
Open Access (DOAJ)
DOI: 10.1162/tacl_a_00257
Aditi S. Krishnapriyan, Joseph Montoya, Maciej Haranczyk, Jens Hummelshøj et al. • Scientific Reports
(2021)
Abstract Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an ...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-021-88027-8
Sebastian Ruder • Arrow@dit (Dublin Institute of Technology)
(2019)
The current generation of neural network-based natural language processing models excels at learning from large amounts of labelled data. Given these capabilities, natural language processing is increasingly applied to new tasks, new domain...
OPENALEX
Open Access
DOI: https://doi.org/10.13025/17598
Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, Thomas Wolf (2019)
The classic supervised machine learning paradigm is based on learning in isolation, a single predictive model for a task using a single dataset. This approach requires a large number of training examples and performs best for well-defined a...
OPENALEX
cc-by
DOI: https://doi.org/10.18653/v1/n19-5004
Xiaozheng Li, Huazhen Wang, Huixin He, Jixiang Du et al. • BMC Bioinformatics
(2019)
Abstract Background Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and deep neural n...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12859-019-2617-8
Christopher D. Manning • Computational Linguistics
(2015)
Deep Learning waves have lapped at the shores of computational linguistics for several years now, but 2015 seems like the year when the full force of the tsunami hit the major Natural Language Processing (NLP) conferences. However, some pun...
OPENALEX
Open Access
DOI: https://doi.org/10.1162/coli_a_00239
Binayak Panda, Sudhanshu Shekhar Bisoyi, Sidhanta Panigrahy • PeerJ Computer Science
(2023)
Dependence on the internet and computer programs demonstrates the significance of computer programs in our day-to-day lives. Such demands motivate malware developers to create more malware, both in terms of quantity and variety. Researchers...
DOAJ
Open Access (DOAJ)
DOI: 10.7717/peerj-cs.1677