Mining symptom and disease web data with NLP and Open Linked Data

2.50
Hdl Handle:
http://hdl.handle.net/10547/623512
Title:
Mining symptom and disease web data with NLP and Open Linked Data
Authors:
Yu, Hong Qing
Abstract:
- Machine Learning (ML) technologies in recent years are widely applied in various areas to assist knowledge gaining and decision-making on healthcare. However, there is no reliable dataset that contains semantic structured knowledge on symptom and disease enable to apply advanced machine learning algorithms such clustering or prediction. In this paper, we propose a framework that can extract data from web with apply Natural Language Processing (NLP) process and semantic annotation to create Open Linked Data (OLD) bas
Affiliation:
University of Bedfordshire
Citation:
Yu H. (2019) 'Mining symptom and disease web data with NLP and Open Linked Data', The 5th World Congress on Electrical Engineering and Computer Systems and Sciences - Lisbon, Avestia Publishing.
Publisher:
Avestia Publishing
Issue Date:
21-Aug-2019
URI:
http://hdl.handle.net/10547/623512
DOI:
10.11159/mvml19.108
Additional Links:
http://avestia.com/EECSS2019_Proceedings/files/paper/MVML/MVML_108.pdf
Type:
Conference papers, meetings and proceedings
Language:
en
Appears in Collections:
Computing

Full metadata record

DC FieldValue Language
dc.contributor.authorYu, Hong Qingen
dc.date.accessioned2019-10-04T09:40:07Z-
dc.date.available2019-10-04T09:40:07Z-
dc.date.issued2019-08-21-
dc.identifier.citationYu H. (2019) 'Mining symptom and disease web data with NLP and Open Linked Data', The 5th World Congress on Electrical Engineering and Computer Systems and Sciences - Lisbon, Avestia Publishing.en
dc.identifier.doi10.11159/mvml19.108-
dc.identifier.urihttp://hdl.handle.net/10547/623512-
dc.description.abstract- Machine Learning (ML) technologies in recent years are widely applied in various areas to assist knowledge gaining and decision-making on healthcare. However, there is no reliable dataset that contains semantic structured knowledge on symptom and disease enable to apply advanced machine learning algorithms such clustering or prediction. In this paper, we propose a framework that can extract data from web with apply Natural Language Processing (NLP) process and semantic annotation to create Open Linked Data (OLD) basen
dc.language.isoenen
dc.publisherAvestia Publishingen
dc.relation.urlhttp://avestia.com/EECSS2019_Proceedings/files/paper/MVML/MVML_108.pdfen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectmachine learningen
dc.subjectsemantic weben
dc.subjectnatural language processingen
dc.subjectLinked Dataen
dc.subjectG560 Data Managementen
dc.titleMining symptom and disease web data with NLP and Open Linked Dataen
dc.typeConference papers, meetings and proceedingsen
dc.contributor.departmentUniversity of Bedfordshireen
dc.date.updated2019-10-04T09:35:17Z-
dc.description.noteOpen access paper https://eecss.org/submissions: "Copyright and Access: The proceedings and related author-guidelines are all based on the open-access model, which means interested individuals and institutions can access the material for free. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this proceedings without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of open access."-
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