A Hypergraph-based Method for Pharmaceutical Data Similarity Retrieval
Authors: 
Mingyue Li, Lixin Du, Jiangying Xu, and Chen GuoAuthors Info & Claims
Mingyue Li, Lixin Du, Jiangying Xu, and Chen GuoAuthors Info & ClaimsSeptember 2021
Pages 134 - 140
Abstract
Drug and compound similarity retrieval is very important for new drug research and development. Most pharmaceutical database provide keyword searching service. Because keyword search method cannot identify entity semantic similarity information, so the retrieval results often got poor drug or compound semantic similarity. In this paper, we propose an attribute semantic similarity retrieval method for pharmaceutical data based on hypergraph and natural language processing technology. Firstly, we use natural language processing technology to research and construct the drug attribute semantic similarity network. Then, we continue building a hypergraph based on drug attribute to get better retrieval efficiency. The experimental results show that, our method can provide similarity retrieval service for researchers.
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Published In
September 2021
189 pages
ISBN:9781450385091
DOI:10.1145/3490322
Copyright © 2021 ACM.
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Association for Computing Machinery
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Published: 27 December 2021
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ICBDT 2021
ICBDT 2021: 2021 4th International Conference on Big Data Technologies
September 24 - 26, 2021
Zibo, China
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