首页|Studies from Queen Mary University of London Further Understanding of Machine Le arning (Synergizing Machine Learning & Symbolic Methods: a Survey On Hybrid Approaches To Natural Language Processing)
Studies from Queen Mary University of London Further Understanding of Machine Le arning (Synergizing Machine Learning & Symbolic Methods: a Survey On Hybrid Approaches To Natural Language Processing)
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Investigators discuss new findings in Machine Learning. According to news reporting out of London, United Kingdom, by NewsRx editors, research stated, "The advancement of machine learning and symbol ic approaches have underscored their strengths and weaknesses in Natural Languag e Processing (NLP). While machine learning approaches are powerful in identifyin g patterns in data, they often fall short in learning commonsense and the factua l knowledge required for the NLP tasks." Financial supporters for this research include UK Research and Innovation as par t of Marie Sklodowska-Curie Actions (MSCA Hybrid Intelligence to monitor, promot e, and analyze transformations in good democracy practices), European Union (EU).
LondonUnited KingdomEuropeCyborgsEmerging TechnologiesMachine LearningNatural Language ProcessingQueen Mar y University of London
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