loading
Papers Papers/2020

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Flora Amato ; Francesco Gargiulo ; Antonino Mazzeo ; Sara Romano and Carlo Sansone

Affiliation: University of Naples Federico II, Italy

Keyword(s): Semantic Processing, Clustering Ensemble.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Cloud Computing ; Data Engineering ; e-Health ; e-Health for Public Health ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Ontologies and the Semantic Web ; Platforms and Applications ; Society, e-Business and e-Government ; Web Information Systems and Technologies

Abstract: The adoption of services for automatic information management is one of the most interesting open problems in various professional and social fields. We focus on the health domain characterized by the production of huge amount of documents, in which the adoption of innovative systems for information management can significantly improve the tasks performed by the actors involved and the quality of the health services offered. In this work we propose a methodology for automatic documents categorization based on the adoption of unsupervised learning techniques. We extracted both semantic and syntactic features in order to define the vector space models and proposed the use of a clustering ensemble in order to increase the discriminative power of our approach. Results on real medical records, digitalized by means of a state-of-the-art OCR technique, demonstrated the effectiveness of the proposed approach.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.232.59.38

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Amato, F.; Gargiulo, F.; Mazzeo, A.; Romano, S. and Sansone, C. (2013). Combining Syntactic and Semantic Vector Space Models in the Health Domain by using a Clustering Ensemble. In Proceedings of the International Conference on Health Informatics - HEALTHINF, (BIOSTEC 2013) ISBN 978-989-8565-37-2; ISSN 2184-4305, pages 382-385. DOI: 10.5220/0004250403820385

@conference{healthinf13,
author={Flora Amato. and Francesco Gargiulo. and Antonino Mazzeo. and Sara Romano. and Carlo Sansone.},
title={Combining Syntactic and Semantic Vector Space Models in the Health Domain by using a Clustering Ensemble},
booktitle={Proceedings of the International Conference on Health Informatics - HEALTHINF, (BIOSTEC 2013)},
year={2013},
pages={382-385},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004250403820385},
isbn={978-989-8565-37-2},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics - HEALTHINF, (BIOSTEC 2013)
TI - Combining Syntactic and Semantic Vector Space Models in the Health Domain by using a Clustering Ensemble
SN - 978-989-8565-37-2
IS - 2184-4305
AU - Amato, F.
AU - Gargiulo, F.
AU - Mazzeo, A.
AU - Romano, S.
AU - Sansone, C.
PY - 2013
SP - 382
EP - 385
DO - 10.5220/0004250403820385