GraphAware Blog - NER

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Deep text understanding combining Graph Models, Named Entity Recognition and Word2Vec

10 Sep 2018 by Dr. Vlasta Kůs, Dr. Alessandro Negro word2vec NLP NER Knowledge Graph

One of the key components of Information Extraction (IE) and Knowledge Discovery (KD) is Named Entity Recognition, which is a machine learning technique that provides us with generalization capabilities based on lexical and contextual information. Named Entities are specific language elements that belong to certain predefined categories, such as persons names, locations, organizations, chemical elements or names of space missions. They are not easy to find and subsequently classify (for example, organizations and space missions share similar formatting and sometimes even context), but having them is of significant help for various tasks:

  • improving search capabilities
  • relating documents among themselves or with external information (such as connecting people in a financial document with information from a business registry)
  • relating causes (e.g weather conditions, accidents, regulatory changes) with effects (e.g. flight or tram delay, stock price changes)

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