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  • 标题:Using Machine Learning Techniques to Gain Insights from Enterprise Unstructured Data
  • 本地全文:下载
  • 作者:Cristian Bucur ; Cristian Bucur
  • 期刊名称:Petroleum-Gas University of Ploiesti Bulletin : Economic Sciences Series
  • 印刷版ISSN:2284-8576
  • 电子版ISSN:2247-8582
  • 出版年度:2019
  • 期号:3
  • 语种:English
  • 出版社:Petroleum-Gas University of Ploiesti
  • 摘要:This article addresses the new IT challenges of business environment in context of Big data.As digitalization extended in all areas and aspects of business processes companies gather huge quantities of data.Business environment realize now that data is an important asset of organization but as studies show most of this data is unstructured so gaining insights is a complex and tedious process.There is now a shift in the way data is processed as new technologies become more accessible to companies.The article presents a practical problem related to document understanding and propose a solution concept and methodology for solving it.Using machine learning and natural language processing has now become a must in dealing with unstructured data for companies that need a competitive advantage.
  • 关键词:big data;machine learning;natural language processing;unstructured data;information retrieval;information extraction;document understanding;named entity recognition;pos tagging
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