Article
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Domain Specific Dictionary between Human and Machine Languages
Version 1
: Received: 20 December 2023 / Approved: 22 December 2023 / Online: 22 December 2023 (08:09:11 CET)
A peer-reviewed article of this Preprint also exists.
Islam, M.S.; Liu, F. Domain-Specific Dictionary between Human and Machine Languages. Information 2024, 15, 144, doi:10.3390/info15030144. Islam, M.S.; Liu, F. Domain-Specific Dictionary between Human and Machine Languages. Information 2024, 15, 144, doi:10.3390/info15030144.
Abstract
In the realm of artificial intelligence, knowledge graphs have become a fascinating area of research. Relationships between entities are depicted through a structural framework in knowledge graphs. In this paper, we propose to build a domain-specific medicine dictionary (DSMD) based on the principles of knowledge graphs. Our dictionary is composed of structured triples, where each entity is defined as a concept, and these concepts are interconnected through relationships. This comprehensive dictionary boasts more than 348,000 triples, encompassing over 20,000 medicine brands and 1,500 generic medicines. It offers a groundbreaking approach to storing and accessing medical data. Our dictionary facilitates various functionalities, including medicine brand information extraction, brand-specific queries, as well as queries involving two words or question answering. We anticipate that our dictionary will serve a broad spectrum of users, catering to both human users, such as diverse range of healthcare professionals as well as AI applications.
Keywords
Knowledge Graph; Medicine Dictionary; Structured Triples; Information Extraction; Question Answering; Artificial Intelligence
Subject
Computer Science and Mathematics, Computer Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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