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研究生: 李怡慧
Lee, Yi-Hui
論文名稱: Search-Based Approach for Automatic Relation Extraction of Disease and Symptom
Search-Based Approach for Automatic Relation Extraction of Disease and Symptom
指導教授: 柯佳伶
Koh, Jia-Ling
學位類別: 碩士
Master
系所名稱: 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2017
畢業學年度: 105
語文別: 英文
論文頁數: 49
中文關鍵詞: medical domain text miningrelation extractionweb-search data
英文關鍵詞: medical domain text mining, relation extraction, web-search data
DOI URL: https://doi.org/10.6345/NTNU202203029
論文種類: 學術論文
相關次數: 點閱:96下載:0
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  • 無中文摘要

    In this thesis, we focus on automatically constructing the relationship between disease and symptoms by online encyclopedia and web search result, including the ranking of the candidate symptoms and the condition of why the symptom is related to that symptom.
    The contribution of this thesis is as follows (1) Search-Based Approach can extract the Conditional Relationship in good performance (2)Conditional Relationship can help user gain more information(3) We build a medical domain Knowledge Base can be implement in NLP tools.

    Chapter 1 Introduction 1 Chapter 2 Related Works 5 2.1 Data Mining in Medical Domain 5 2.2 Automatic Knowledge Extraction 6 2.3 Knowledge Base Completion 7 2.4 Conditional Knowledge Base 8 Chapter 3 Relation Extraction 9 3.1 Relation Extraction Problem Definition 9 3.2 Seed Diseases and Symptoms Relationship Construction 12 3.3 Extended Disease and Symptoms Relationship Construction 13 Chapter 4 Conditional Disease and Symptoms Relationship Construction 20 4.1 Conditional Terms Generation 20 4.2 Represent Conditional Term Generation 21 Chapter 5 Evaluation 26 5.1 Data Description 26 5.2 Disease and Symptoms Relationship Evaluation 27 5.3 Conditional Terms Evaluation 35 Chapter 6 Conclusion 42 References 43 Appendixes 46

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