Conditional Relationship Extraction for Diseases and Symptoms by a Web Search-Based Approach

Yi Hui Lee, Jia Ling Koh

研究成果: 書貢獻/報告類型會議論文篇章

1 引文 斯高帕斯(Scopus)

摘要

This paper studies the strategies of automatically extracting the conditional relationships between diseases and symptoms from a Chinese encyclopedia site and the disease-related web pages searched from the Internet. At first, the seed symptoms of a disease are extracted from an online medical encyclopedia automatically. These seed symptoms are utilized as query keywords to automatically find more symptoms of a disease from the unstructured documents of the disease-related search results. Next, a jointly learning method is used to construct the embedded representations of the conditional terms and pattern terms. Besides, the semantic similarity matrix of conditional terms is computed through the co-clustering algorithm to discover the representative conditional terms of the clusters. The result of experiments shows that the proposed method, which discovers the semantically related symptoms of a disease associated with conditionals, achieves high accuracy. Besides, many unusually known symptoms considered by the medical experts are discovered, which may be noticeable symptoms needing further verification in the future.

原文英語
主出版物標題Proceedings - 2018 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2018
發行者Institute of Electrical and Electronics Engineers Inc.
頁面554-561
頁數8
ISBN(電子)9781538673256
DOIs
出版狀態已發佈 - 2019 一月 10
事件18th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2018 - Santiago, 智利
持續時間: 2018 十二月 32018 十二月 6

出版系列

名字Proceedings - 2018 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2018

會議

會議18th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2018
國家智利
城市Santiago
期間2018/12/032018/12/06

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications

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