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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

Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review

Jiaqi Fu, Chaixiu Li, Chunlan Zhou, Wenji Li et al. • Journal of Medical Internet Research (2023)

BackgroundGiven the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews ...

DOAJ Open Access (DOAJ) DOI: 10.2196/43349

A fault location method for secondary virtual circuits in smart substations based on the integration of GAE and GCN

Yuxi Wang, Yue Wang, Sha Han • Discover Artificial Intelligence (2026)

Abstract The secondary virtual circuits in smart substations enable digital and networked information exchange between devices. However, their extensive logical connections, complex structure, and implicit interdependencies pose significant...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-02248-2

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

Contagions

Paolo Pepe • Testo & Senso (2022)

A hundred years separate two of the most successful masterpieces of English Gothic Fiction: The Monk (1796) by Matthew Gregory Lewis and Dracula (1897) by Bram Stoker. The significance of this circumstance goes beyond the mere chronological...

DOAJ Open Access (DOAJ)

Adversarial Attacks on Deep-learning Models in Natural Language Processing

Wei Emma Zhang, Quan Z. Sheng, Ahoud Alhazmi, Chenliang Li • ACM Transactions on Intelligent Systems and Technology (2020)

With the development of high computational devices, deep neural networks (DNNs), in recent years, have gained significant popularity in many Artificial Intelligence (AI) applications. However, previous efforts have shown that DNNs are vulne...

OPENALEX Open Access DOI: https://doi.org/10.1145/3374217

Biomedical Natural Language Processing

Kevin Bretonnel Cohen, Dina Demner‐Fushman • Natural language processing (2014)

Biomedical Natural Language Processing is a comprehensive tour through the classic and current work in the field. It discusses all subjects from both a rule-based and a machine learning approach, and also describes each subject from the per...

OPENALEX DOI: https://doi.org/10.1075/nlp.11

Natural Language Processing

Yue Zhang, Zhiyang Teng • Cambridge University Press eBooks (2020)

With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are sy...

OPENALEX DOI: https://doi.org/10.1017/9781108332873

Connectionist Approaches to Natural Language Processing

Chris Sinha, Ronan G. Reilly, NOEL E. SHARKEY • The American Journal of Psychology (1994)

Preface, N. Sharkey and R. Reilly connectionist natural language processing semantics, M.D. Dyer, et al distributed symbol discovery through symbol recirculation - toward natural language processing in distributed connectionist networks, R....

OPENALEX DOI: https://doi.org/10.2307/1423043

Analyzing Brain Tumor Classification Techniques: A Comprehensive Survey

Pratikkumar Chauhan, Munindra Lunagaria, Deepak Kumar Verma, Krunal Vaghela et al. • IEEE Access (2024)

Classification of brain tumour is critical in medical image analysis and diagnosis as it aids in determining the affinity of cases to select treatment paths. This feature underscores the importance of accurate classification of brain tumour...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3460380

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 future

M. Chandhana Surabhi • International Conference on Optical Imaging Sensor and Security (ICOSS) (2013)

Natural Language Processing is a technique where machine can become more human and thereby reducing the distance between human being and the machine can be reduced. Therefore in simple sense NLP makes human to communicate with the machine e...

OPENALEX DOI: https://doi.org/10.1109/icoiss.2013.6678407

Attention Pooling-Based Bidirectional GRU Model for Sentimental Classification

Dejun Zhang, Mingbo Hong, Lu Zou, Fei Han et al. • International Journal of Computational Intelligence Systems

Recurrent neural network (RNN) is one of the most popular architectures for addressing variable sequence text, and it shows outstanding results in many natural language processing (NLP) tasks and remarkable performance in capturing long-ter...

DOAJ Open Access (DOAJ) DOI: 10.2991/ijcis.d.190710.001