Semantic Cluster Labeling for Medical Relations

  • Anita AlicanteEmail author
  • Anna Corazza
  • Francesco Isgrò
  • Stefano Silvestri
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 60)


In the context of the extraction of the semantic contents important for the effective exploitation of the documents which are now made available by medical information systems, we consider the processing of relations connecting named entities and propose an unsupervised approach to their recognition and labeling. The approach is applied to an Italian data set of medical reports, and interesting results are presented and discussed from a qualitative point of view.


Feature Vector Cosine Similarity Entity Recognition Medical Information System Entity Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Anita Alicante
    • 1
    Email author
  • Anna Corazza
    • 1
  • Francesco Isgrò
    • 1
  • Stefano Silvestri
    • 2
  1. 1.Dip. di Ingegneria Elettrica e delle Tecnologie dell’Informazione (DIETI)Università degli Studi di Napoli Federico IINapoliItaly
  2. 2.Dip. di Medicina SperimentaleSeconda Università degli Studi di NapoliCasertaItaly

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