A sequential graph neural network for short text classification
Short text classification is an important problem of natural language processing (NLP), and
graph neural networks (GNNs) have been successfully used to solve different NLP …
graph neural networks (GNNs) have been successfully used to solve different NLP …
Domain-specific term extraction: a case study on Greek Maritime legal texts
Preservation of cultural heritage has significantly attracted many research efforts. Amongst
them, significant interest has been presented to sharing of cultural heritage content, whereas …
them, significant interest has been presented to sharing of cultural heritage content, whereas …
Comparative Study of Recurrent and Dense Neural Networks for Classifying Maritime Terms
D Mouratidis, K Kermanidis… - 2023 14th International …, 2023 - ieeexplore.ieee.org
Despite its importance, the extraction of domain-specific terms has not been sufficiently
studied. This paper proposes an automated approach for semi-supervised term extraction …
studied. This paper proposes an automated approach for semi-supervised term extraction …
A Comparative Study of Machine Learning Methods and Text Features for Text Authorship Recognition in the Example of Azerbaijani Language Texts
R Azimov, E Providas - Algorithms, 2024 - mdpi.com
This paper presents various machine learning methods with different text features that are
explored and evaluated to determine the authorship of the texts in the example of the …
explored and evaluated to determine the authorship of the texts in the example of the …
Innovative deep neural network fusion for pairwise translation evaluation
A language independent deep learning (DL) architecture for machine translation (MT)
evaluation is presented. This DL architecture aims at the best choice between two MT (S1 …
evaluation is presented. This DL architecture aims at the best choice between two MT (S1 …
Comparing a hand-crafted to an automatically generated feature set for deep learning: pairwise translation evaluation
D Mouratidis, KL Kermanidis - Proceedings of the Human …, 2019 - aclanthology.org
The automatic evaluation of machine translation (MT) has proven to be a very significant
research topic. Most automatic evaluation methods focus on the evaluation of the output of …
research topic. Most automatic evaluation methods focus on the evaluation of the output of …
Training set enlargement using binary weighted interpolation maps for the single sample per person problem in face recognition
We propose a method of enlarging the training dataset for a single-sample-per-person
(SSPP) face recognition problem. The appearance of the human face varies greatly, owing …
(SSPP) face recognition problem. The appearance of the human face varies greatly, owing …
Innovatively fused deep learning with limited noisy data for evaluating translations from poor into rich morphology
Evaluation of machine translation (MT) into morphologically rich languages has not been
well studied despite its importance. This paper proposes a classifier, that is, a deep learning …
well studied despite its importance. This paper proposes a classifier, that is, a deep learning …
NoDeeLe: A Novel Deep Learning Schema for Evaluating Neural Machine Translation Systems
Due to the wide-spread development of Machine Translation (MT) systems–especially
Neural Machine Translation (NMT) systems–MT evaluation, both automatic and human, has …
Neural Machine Translation (NMT) systems–MT evaluation, both automatic and human, has …
[PDF][PDF] A Review of Credit Card Fraud Detection Using Machine Learning Algorithms
AG Oketola, T Gbadebo-Ogunmefun, A Agbeja - researchgate.net
Research on fraud detection using machine learning in credit card problems has received
high attention. The paper considers using popular supervised algorithms for classification …
high attention. The paper considers using popular supervised algorithms for classification …