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Showing 20 of 88 academic articles

Leveraging sentiment analysis of food delivery services reviews using deep learning and word embedding

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

Optimising Contextual Embeddings for Meaning Conflation Deficiency Resolution in Low-Resourced Languages

Mosima A. Masethe, Sunday O. Ojo, Hlaudi D. Masethe • Computers (2025)

Meaning conflation deficiency (MCD) presents a continual obstacle in natural language processing (NLP), especially for low-resourced and morphologically complex languages, where polysemy and contextual ambiguity diminish model precision in ...

DOAJ Open Access (DOAJ) DOI: 10.3390/computers14090402

Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach

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

Enhancing educational semantic retrieval through dual objective fine tuning of open source embedding models

Ramteja Sajja, Yusuf Sermet, Ibrahim Demir • Discover Education (2026)

Abstract Recent advances in AI have catalyzed the adoption of intelligent educational tools, yet many semantic retrieval systems remain ill-suited to the unique linguistic and structural characteristics of academic content. This study prese...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44217-026-01825-y

Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)

Mariya Toneva, Leila Wehbe • arXiv (Cornell University) (2019)

Neural networks models for NLP are typically implemented without the explicit encoding of language rules and yet they are able to break one performance record after another. This has generated a lot of research interest in interpreting the ...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1905.11833

Natural Language Processing

Pramod Kumar Singh • Apress eBooks (2018)

This chapter uncovers some of the basic techniques to tackle text data using PySpark. Today's textual form of data is being generated at a lightning pace with multiple social media platforms offering users the options to share their opinion...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-4131-8_9

Detecting Fake News in Urdu Language Using Machine Learning, Deep Learning, and Large Language Model-Based Approaches

Muhammad Shoaib Farooq, Syed Muhammad Asadullah Gilani, Muhammad Faraz Manzoor, Momina Shaheen • Information (2025)

Fake news is false or misleading information that looks like real news and spreads through traditional and social media. It has a big impact on our social lives, especially in politics. In Pakistan, where Urdu is the main language, finding ...

DOAJ Open Access (DOAJ) DOI: 10.3390/info16070595

Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks

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

Analysis and Classification of Word Co-Occurrence Networks From Alzheimer’s Patients and Controls

Tristan Millington, Saturnino Luz • Frontiers in Computer Science (2021)

In this paper we construct word co-occurrence networks from transcript data of controls and patients with potential Alzheimer’s disease using the ADReSS challenge dataset of spontaneous speech. We examine measures of the structure of these ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcomp.2021.649508

Transfer Learning in Natural Language Processing

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

La focalisation des conditionnelles

Gilles Corminboeuf • Discours (2014)

The aim of this article is to identify the different syntactic modes existing in French to focus if-clauses in constructions such as {if-P, Q}, and {Q if-P}. It is not irrelevant to consider that if-clauses may occupy a focus position, seei...

DOAJ Open Access (DOAJ) DOI: 10.4000/discours.8903

Fruit freshness detection based on multi-task convolutional neural network

Yinsheng Zhang, Xudong Yang, Yongbo Cheng, Xiaojun Wu et al. • Current Research in Food Science (2024)

Background: Fruit freshness detection by computer vision is essential for many agricultural applications, e.g., automatic harvesting and supply chain monitoring. This paper proposes to use the multi-task learning (MTL) paradigm to build a d...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.crfs.2024.100733

A comprehensive analytical assessment of dino-based architectures for sustainable automated potato inspection in the Al Kharj Region

Zahraa Tarek, Esraa Hasan • Journal of the Saudi Society of Agricultural Sciences (2026)

Abstract Self-supervised learning (SSL) has emerged as a pivotal paradigm in computer vision, particularly for applications where labeled data are limited, costly, or labor-intensive to obtain. This paradigm is especially relevant to sustai...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44447-026-00151-x