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Semantic cluster labeling for medical relations

Conference Paper
Publication Date:
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.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Clustering; Word Embeddings; Relation Classification
List of contributors:
Silvestri, Stefano
Authors of the University:
SILVESTRI STEFANO
Handle:
https://iris.cnr.it/handle/20.500.14243/339297
Published in:
SMART INNOVATION, SYSTEMS AND TECHNOLOGIES (PRINT)
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URL

http://www.scopus.com/record/display.url?eid=2-s2.0-84979072407&origin=inward
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