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Leveraging Semantic Similarity for Non-Conformity management in industrial environments
LOPEZ, YADINI PEREZ; DA SILVA CALDAS, ABRAÃO JONAS; RIBEIRO, LAURA MICHAELLA BATISTA
Resumo
Resumo
In this work we explore the use of semantic similarity techniques to enhance the management of Non-Conformity in emerging industrial environments. Small and new companies lack historical data which makes unfeasible the application of Machine Learning-based solutions for data processing. Regarding this, we investigate the usage of training-independent semantic similarity techniques for Non-Conformity matching. Specifically, we compared two text vectorization methods, Term Frequency-Inverse Document Frequency and the Word2vec model combined with the cosine distance algorithm to reduce the amount of Non-Conformity to be processed by human specialists automatically finding the reports that point out the same quality issue.
Autoria
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palavras-chave
Palavras-chave
semantic similarityquality reportstext vectorizationTF-IDFWord2Veccosine similaritysmall businessmanufacturing quality management
Status
Published
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Trabalho em anais de evento