• “FabNER”: information extraction from manufacturing process science domain literature using named entity recognition

    1 month ago - By Springer

    Abstract
    The number of published manufacturing science digital articles available from scientific journals and the broader web have exponentially increased every year since the 1990s. To assimilate all of this knowledge by a novice engineer or an experienced researcher, requires significant synthesis of the existing knowledge space contained within published material, to find answers to basic and complex queries. Algorithmic approaches through machine learning and specifically Natural Language Processing on a domain specific area such as manufacturing, is lacking. One of the significant...
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