A Framework of NLP Based Information Tracking and Related Knowledge Organizing with Topic Maps

This paper presents a computational framework for information extraction and aggregation which aims to integrate and organize the data/information resources that spread throughout the Internet in the manner that makes them useful for tracking events such as natural disaster, and disease dispersion....

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Detalles Bibliográficos
Autores principales: Kawtrakul, Asanee, Yingsaeree, Chaiyakorn, Andres, Frederic
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2007
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122097/
http://dx.doi.org/10.1007/978-3-540-73351-5_24
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author Kawtrakul, Asanee
Yingsaeree, Chaiyakorn
Andres, Frederic
author_facet Kawtrakul, Asanee
Yingsaeree, Chaiyakorn
Andres, Frederic
author_sort Kawtrakul, Asanee
collection PubMed
description This paper presents a computational framework for information extraction and aggregation which aims to integrate and organize the data/information resources that spread throughout the Internet in the manner that makes them useful for tracking events such as natural disaster, and disease dispersion. We introduce a simple statistical information extraction technique for summarizing the document into a predefined structure. We apply the topic maps approach as a semantic layer in aggregating and organizing the extracted information for smart access. In addition, this paper also carries out a case study on disease dispersion domain using the proposed framework.
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spelling pubmed-71220972020-04-06 A Framework of NLP Based Information Tracking and Related Knowledge Organizing with Topic Maps Kawtrakul, Asanee Yingsaeree, Chaiyakorn Andres, Frederic Natural Language Processing and Information Systems Article This paper presents a computational framework for information extraction and aggregation which aims to integrate and organize the data/information resources that spread throughout the Internet in the manner that makes them useful for tracking events such as natural disaster, and disease dispersion. We introduce a simple statistical information extraction technique for summarizing the document into a predefined structure. We apply the topic maps approach as a semantic layer in aggregating and organizing the extracted information for smart access. In addition, this paper also carries out a case study on disease dispersion domain using the proposed framework. 2007 /pmc/articles/PMC7122097/ http://dx.doi.org/10.1007/978-3-540-73351-5_24 Text en © Springer-Verlag Berlin Heidelberg 2007 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Kawtrakul, Asanee
Yingsaeree, Chaiyakorn
Andres, Frederic
A Framework of NLP Based Information Tracking and Related Knowledge Organizing with Topic Maps
title A Framework of NLP Based Information Tracking and Related Knowledge Organizing with Topic Maps
title_full A Framework of NLP Based Information Tracking and Related Knowledge Organizing with Topic Maps
title_fullStr A Framework of NLP Based Information Tracking and Related Knowledge Organizing with Topic Maps
title_full_unstemmed A Framework of NLP Based Information Tracking and Related Knowledge Organizing with Topic Maps
title_short A Framework of NLP Based Information Tracking and Related Knowledge Organizing with Topic Maps
title_sort framework of nlp based information tracking and related knowledge organizing with topic maps
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122097/
http://dx.doi.org/10.1007/978-3-540-73351-5_24
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