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RLPMTM 2021 : Applied Sciences special issue Rich Linguistic Processing for Multilingual Text Mining

Submission Deadline: Jan 11, 2021

About

Natural language processing and text mining technologies have experienced a revolution in the last few years, with substantial improvements in accuracy mainly due to the use of deep-learning neural networks and large pretrained models relying on huge amounts of data. Explicit representations of linguistic knowledge (such as parse trees, semantic dependencies, lexicons, linguistic rules, etc.) have lost their protagonist role in systems where neural networks perform the bulk of the task, often in an end-to-end fashion. However, it is far from guaranteed that the accuracy improvement gains from the advances in neural architectures will not plateau, as in previous occasions, highlighting the need to combine them with rich linguistic processing. Furthermore, end-to-end neural systems have limitations, especially in a context of multilingualism where low-resource languages are involved: black-box nature with limited explainability, data-induced bias, reliance on large amounts of data that may be unavailable for many of the thousands of languages existing in the world, high computational requirements, and large energy usage and contribution to global warming.

Call For Paper

Keywords

  • Natural language processing
  • Multilingual language processing
  • Language resources
  • Linguistic knowledge
  • Text mining
  • Information retrieval
  • Sentiment analysis
  • Recommender systems
  • Explainable artificial intelligence
  • Data-induced bias in NLP systems

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