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博碩士論文 etd-0124117-093945 詳細資訊
Title page for etd-0124117-093945
Ontology-Based Semantic Q&A system in Health Care: An Illustrated Application on Down Syndrome
Year, semester
Number of pages
Te-Min Chang,
Advisory Committee
蕭文峰, 徐銘甫, 林欣瑾
Wen-Feng Hsiao; Ming-Fu Hsu; Sin-Jin Lin
Date of Exam
Date of Submission
Natural language process, Healthcare, Synonyms, Ontology, Semantic Q&A system
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The thesis/dissertation has been browsed 5937 times, has been downloaded 924 times.
This study presents an ontology-based Semantic Question and Answer (Q&A) system applied to the Down Syndrome in Healthcare. We proposed a Q&A system which allows for users to ask questions in natural language, and the system will search the answers from the ontology by reasoning with related keywords from the natural language searched. In order to figure out what users’ questions meant we use the Classified Knowledge and Information Processing (CKIP) to tokenize words and to tag Part-Of-Speech (POS) in the questions. This Q&A system also uses a combination of three keywords, including medical terminologies, intention words which only exist in the domain of Medicine, and words of 5W1H, to analyze natural language questions. These three kinds of keywords allow our approach of answer extraction to reason in the ontology by formulated SPARQL queries. This system has been developed and tested in the Chinese language. The ontology is being adopted for classifying Down syndrome related information. We have carried out experiments to evaluate our approach of question analysis and answer extraction. The preliminary result shows that the excellent performance of our proposed approach.
目次 Table of Contents
1. Introduction + 1
1.1 Background + 1
1.2 Motivation + 3
2. Related works + 6
2.1 Question and Answer System + 6
2.1.1 Question Analysis + 6
2.1.2 Answers Analysis + 7
2.2 NLP-based Q&A system + 9
2.2.1 Lexical Analysis + 9
2.2.2 Semantic Analysis + 10
2.3 Semantic Web + 12
2.3.1 Ontology + 13
2.3.2 Building Ontology + 14
2.3.3 Application based on Ontology + 15
3. The Approach + 17
3.1 Skeleton of our Approach + 17
3.2 Question Analysis + 19
3.2.1 Word tokenization and Part of Speech (POS) Tagging in Chinese + 21
3.2.2 Keywords Identify + 21
3.3 Answer Extract + 26
3.3.1 SPARQL Queries + 26
3.4 Building Ontology + 31
4. Evaluation + 38
4.1 Evaluation of our approaches + 38
4.2 Evaluated with Different system + 40
5.Conclusion + 46
Reference + 49
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