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.

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[2] Feldman, Ronen, et al. "Utilizing text mining on online medical forums to predict label change due to adverse drug reactions." Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, 2015.
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[9] Goodwin, Travis R., and Sanda M. Harabagiu. "Medical Question Answering for Clinical Decision Support." Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. ACM, 2016.
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[11] West, Robert, et al. "Knowledge base completion via search-based question answering." Proceedings of the 23rd international conference on World wide web. ACM, 2014.
[12] Wang, Pengwei, et al. "Learning to Extract Conditional Knowledge for Question Answering using Dialogue." Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. ACM, 2016.
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[15] Li, Mingyang, et al. "Building a Large-Scale Cross-Lingual Knowledge Base from Heterogeneous Online Wikis." National CCF Conference on Natural Language Processing and Chinese Computing. Springer International Publishing, 2015.
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[19] 140.122.184.134/DAS/thesis_index.php