政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/125531

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/125531

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题名:	線上論壇提問推薦機制：以醫療照護問答網站為例 A posting recommendation system for question formulation: A healthcare Q&A forum study
作者:	陳怡儒 Chen, Yi-Ju
贡献者:	林怡伶 Lin, Yi-Ling 陳怡儒 Chen, Yi-Ju
关键词:	問答論壇醫療資訊學推薦系統主題式推薦系統詞向量語意關聯 Word2Vec WordNet 使用者生成內容設計科學使用者研究廣義估計式 Question-answering forum Healthcare informatics Recommendation system Topic-based recommendation Word embedding Semantic relatedness Word2Vec WordNet User-generated content Design science User study Generalized estimating equations
日期:	2019
上传时间:	2019-09-05 15:45:08 (UTC+8)
摘要:	搜尋引擎是現代人慣用搜尋解答的工具，但不是所有人皆可以在搜索引擎上透過精準的查詢句或關鍵字快速找到所需的資訊。有別於搜尋引擎，線上問答論壇並未限制使用者如何提出問題才能找到答案，自由式的書寫環境逐漸吸引許多用戶到平台上尋找有用的資訊，並解決他們在特定領域遇到的困難。然而使用者生成內容不可避免會有表達不清的問題，尤其是特定領域的提問。因為提問者通常不具備專業背景，進而讓論壇分類系統無法成功匹配或是提問目的模糊而得不到專業人士的解答。所以我們設計出一個貼文撰寫推薦系統希望能提高線上論壇的可用性。常見的推薦機制傾向於匹配合適的回覆者或向用戶提出已存在的相似問題，但沒有人去研究如何在詢問過程中撰寫優良的貼文。本文將著重於醫療保健案例中，使用新式推薦系統是否能優化提問者的貼文。我們採用設計科學的方法來完成貼文撰寫主題式推薦系統的研究。目標是協助用戶更了解自己的疑問以組織想法來寫出不錯的貼文，最終獲得有效的答案。我們的推薦系統會透過使用者研究的方式，聘請27名參與者，在兩種保健情境下使用三種模型進行廣義估計式分析，了解使用者是否會因為推薦系統而去優化撰寫的貼文。此外，我們招募兩名從事醫療職業相關的專家，請他們對推薦系統修改後的貼文作評分，驗證是否能讓專家迅速解決問題。我們的結果說明，即使主題式推薦系統的可用性仍需要更多證據來證明，貼文撰寫推薦系統的表現確實與不具備推薦系統的貼文撰寫情況不同。其次，兩位專家評分的結果顯示，添加更多病況資訊並使用貼文撰寫主題式推薦系統，的確增加了獲得更高分評價的可能性。雖然此篇論文遇到了一些問題無法直接證實我們目前主題式的設計可行，不過我們確定了協助寫作貼文的推薦機制是值得探討的。對於常需要協助提問者的服務提供方，優化貼文的機制將能協助服務方製作常見問題與解答，並在撰寫過程中引導提問者至解答頁面，儘速解決問題。 People are getting used to google when they confuse about something, but the truth is not everyone can formulate clear queries on a search engine. Different from the search engine, online Q&A forums allow people to write anything and any styles they want. This free-writing environment gradually attracts more users to search for useful information and deal with their difficulties of specific domains on this platform. However, we cannot control the quality of user-generated content. Few askers have professional backgrounds, so unclear posts may be categorized wrong by supportive systems or difficult to be understood by experts. So, we design a posting recommender and expect it can improve the usability of online forums. In the past, recommendation mechanisms matched suitable repliers or suggested similar questions to users, but no one investigated how to write better posts. This thesis focuses on a new recommendation system to support askers optimizing posts under a healthcare study. We apply the design science methodology to develop a topic-based posting recommender. Its goal is to support users in understanding more about self-issues, organizing thoughts to write reasonable posts and then receiving effective answers. Our posting recommender is evaluated by generalized estimating equations with a user study containing 27 participants, three models, and two healthcare conditions to see if users become more engaged in the question generation. In addition, we recruited two medical-related experts to verify whether modified posts attract them to answer quickly by rating posts from participants. Though the usefulness of our posting recommender still needs more evidence to prove, the result indicates that the performance of a posting recommender acts differently from not having the recommendation system. Another result of analysing experts shows adding more information and using a posting recommender enhance the possibility to get higher rating points. The thesis does encounter some problems to confirm the design effectiveness at this stage, but the posting recommender is proved to be worth investigating. Those who need more efforts to deal with askers may think the posting recommender mechanism useful. The mechanism of optimized posts can help service provider arrange frequently asked questions and guide askers to find the correct answer before posting.
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描述:	碩士國立政治大學資訊管理學系 106356025
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0106356025
数据类型:	thesis
DOI:	10.6814/NCCU201900771
显示于类别:	[資訊管理學系] 學位論文

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