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.

Semantic cluster labeling for medical relations

Silvestri Stefano
2016

Abstract

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.
2016
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
9783319396866
Clustering
Word Embeddings
Relation Classification
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/339297
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