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Preface to the Special Issue “Natural Language Processing (NLP) and Machine Learning (ML)—Theory and Applications”

Author

Listed:
  • Florentina Hristea

    (Department of Computer Science, Faculty of Mathematics and Computer Science, University of Bucharest, 010014 Bucharest, Romania)

  • Cornelia Caragea

    (Department of Computer Science, University of Illinois at Chicago, Chicago, IL 60607, USA)

Abstract

Natural language processing (NLP) is one of the most important technologies in use today, especially due to the large and growing amount of online text, which needs to be understood in order to fully ascertain its enormous value [...]

Suggested Citation

  • Florentina Hristea & Cornelia Caragea, 2022. "Preface to the Special Issue “Natural Language Processing (NLP) and Machine Learning (ML)—Theory and Applications”," Mathematics, MDPI, vol. 10(14), pages 1-5, July.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:14:p:2481-:d:864331
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    References listed on IDEAS

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    1. Santosh Kumar Banbhrani & Bo Xu & Hongfei Lin & Dileep Kumar Sajnani, 2022. "Taylor-ChOA: Taylor-Chimp Optimized Random Multimodal Deep Learning-Based Sentiment Classification Model for Course Recommendation," Mathematics, MDPI, vol. 10(9), pages 1-26, April.
    2. Sergiu Nisioi & Ana Sabina Uban & Liviu P. Dinu, 2022. "Identifying Source-Language Dialects in Translation," Mathematics, MDPI, vol. 10(9), pages 1-14, April.
    3. Ismail Badache & Adrian-Gabriel Chifu & Sébastien Fournier, 2022. "Unsupervised and Supervised Methods to Estimate Temporal-Aware Contradictions in Online Course Reviews," Mathematics, MDPI, vol. 10(5), pages 1-24, March.
    4. Mihailo Škorić & Ranka Stanković & Milica Ikonić Nešić & Joanna Byszuk & Maciej Eder, 2022. "Parallel Stylometric Document Embeddings with Deep Learning Based Language Models in Literary Authorship Attribution," Mathematics, MDPI, vol. 10(5), pages 1-27, March.
    5. Edoardo Savini & Cornelia Caragea, 2022. "Intermediate-Task Transfer Learning with BERT for Sarcasm Detection," Mathematics, MDPI, vol. 10(5), pages 1-14, March.
    6. Laura Burdick & Jonathan K. Kummerfeld & Rada Mihalcea, 2021. "To Batch or Not to Batch? Comparing Batching and Curriculum Learning Strategies across Tasks and Datasets," Mathematics, MDPI, vol. 9(18), pages 1-11, September.
    7. Christopher Haynes & Marco A. Palomino & Liz Stuart & David Viira & Frances Hannon & Gemma Crossingham & Kate Tantam, 2022. "Automatic Classification of National Health Service Feedback," Mathematics, MDPI, vol. 10(6), pages 1-23, March.
    8. Mihai Masala & Stefan Ruseti & Traian Rebedea & Mihai Dascalu & Gabriel Gutu-Robu & Stefan Trausan-Matu, 2021. "Identifying the Structure of CSCL Conversations Using String Kernels," Mathematics, MDPI, vol. 9(24), pages 1-21, December.
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