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Natural Language Processing (almost) from Scratch

Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen et al. • arXiv (Cornell University) (2011)

We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including: part-of-speech tagging, chunking, named entity recognition, and semantic role labeling. This...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1103.0398

Natural Language Processing Recipes

Akshay Kulkarni, Adarsha Shivananda • Apress eBooks (2019)

Implement natural language processing applications with Python in this problem-solution book. Here, coding exercises will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identi...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-4267-4

Five sources of bias in natural language processing

Dirk Hovy, Shrimai Prabhumoye • Language and Linguistics Compass (2021)

Recently, there has been an increased interest in demographically grounded bias in natural language processing (NLP) applications. Much of the recent work has focused on describing bias and providing an overview of bias in a larger context....

OPENALEX cc-by-nc DOI: https://doi.org/10.1111/lnc3.12432 PMC: 9285808

Datasets: A Community Library for Natural Language Processing

Quentin Lhoest, A. Villanova del Moral, Yacine Jernite, Abhishek Thakur et al. • Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP) (2021)

Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, Abhishek Thakur, Patrick von Platen, Suraj Patil, Julien Chaumond, Mariama Drame, Julien Plu, Lewis Tunstall, Joe Davison, Mario Šaško, Gunjan Chhablani, Bhavitvya Malik, Simon Bra...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/2021.emnlp-demo.21

Natural Language Processing (Almost) from Scratch

CollobertRonan, WestonJason, BottouLéon, KarlenMichael et al. • Journal of Machine Learning Research (2011)

We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including part-of-speech tagging, chunking, named entity rec......

OPENALEX DOI: https://doi.org/10.5555/1953048.2078186

Natural Language Processing

Abhimanyu Chopra, Abhinav Prashar, Chandresh Sain • Natural language processing (2013)

ABSTRACT: Language is way of communicating your words Language helps in understanding the world,we get a better insight of the world. Language helps speakers to be as vague or as precise as they like. NLP Stands for natural language process...

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

Historical Models and Serial Sources

Michael Piotrowski • Journal of European Periodical Studies (2019)

Serial sources such as records, registers, and inventories are the ‘classic’ sources for quantitative history. Unstructured, narrative texts such as newspaper articles or reports were out of reach for historical analyses, both for practical...

DOAJ Open Access (DOAJ) DOI: 10.21825/jeps.v4i1.10226

Natural Language Processing for Smart Healthcare

Binggui Zhou, Guanghua Yang, Zheng Shi, Shaodan Ma • IEEE Reviews in Biomedical Engineering (2022)

Smart healthcare has achieved significant progress in recent years. Emerging artificial intelligence (AI) technologies enable various smart applications across various healthcare scenarios. As an essential technology powered by AI, natural ...

OPENALEX Open Access DOI: https://doi.org/10.1109/rbme.2022.3210270

HuggingFace's Transformers: State-of-the-art Natural Language Processing

Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond et al. • arXiv (Cornell University) (2019)

Recent progress in natural language processing has been driven by advances in both model architecture and model pretraining. Transformer architectures have facilitated building higher-capacity models and pretraining has made it possible to ...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1910.03771