Knowledge Extraction from Healthcare Data Using User-Adaptable Keywords-Based Query Language
Pages 128 - 131
Abstract
Nowadays, the volume of the information gathered by any organization increases more and more rapidly. It is essential to be able to use this information efficiently for it to benefit the operation of the organization. There is no point of gathering the information if it is not converted into knowledge. The knowledge extraction process becomes the backbone of any successful organization. Moreover, the extraction of the knowledge must be quick and efficient, so that the newly-obtained knowledge can be put in use at once. The problem addressed in this paper is how to allow the domain expert to extract the knowledge from their information systems themselves without involving the third party in the form of an IT specialist. This goal is of utmost importance for the domain experts, e.g. hospital managers and physicians, because they need to make decisions based on the available knowledge and to do it rapidly and efficiently. We propose a system in this paper that allows formulating queries in the natural language and that also adapts to the specifics of the user. Our experiments show that such kind of querying could provide an improvement in the decision-making process of healthcare professionals.
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- Knowledge Extraction from Healthcare Data Using User-Adaptable Keywords-Based Query Language
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Published In
May 2020
170 pages
ISBN:9781450377652
DOI:10.1145/3404663
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Published: 10 July 2020
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ICISDM 2020
ICISDM 2020: 2020 the 4th International Conference on Information System and Data Mining
May 15 - 17, 2020
HI, Hawaii, USA
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