Machine Learning and Natural Language Processing (ML & NLP)

Dear Colleagues,

The Special Issue “Machine learning and Natural Language Processing (ML & NLP)” is dedicated to the modelization of predictive tasks and classification tasks on different types of texts.

The Special Issue is concerned with textmining and natural language processing, which comprises, among other things:

- Ontology, embeddings (static), transformers (contextual embeddings), NER (named entities recognition), text classification, text generation (GAN), text summarization, word clustering, sentiment analysis, pattern recognition, tagging/annotations, document summarization, entity extraction, etc.

The Special Issue is dedicated to the modelization (statistical models) applied to texts, such as supervised and non-supervised models, and algorithms that help to identify patterns in texts. 

A special focus could be placed on explainable artificial intelligence (XAI), i.e., neural networks applied to texts in order to determine words and sentences that contribute to the prediction/classification made by the neural network.

Applications to all kinds of texts is welcome, and in this respect many fields may be covered: health, biomedical research, law, jurimetrics, economics, finance, etc.

This research is funded by the French National Research Agency: ANR LAWBOT ANR-20-CE38-0013.

Prof. Dr. Stéphane Mussard
Guest Editor

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