整合網路口碑之個人化醫療院所推薦系統-以牙醫診所為例

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陳麗娟(Li-chuan Chen) 查詢紙本館藏

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資訊管理學系

論文名稱

整合網路口碑之個人化醫療院所推薦系統-以牙醫診所為例
(An online word-of-mouth based recommender system for dental services)

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摘要(中)

網路口碑已成為消費者尋找醫療院所的一個重要依據，但隨著網路上分享的資訊越來越多，從大量口碑中找到自己所需的資訊已變成一項費時的任務。因此口碑推薦系統成為各大網站必備工具，雖然口碑已被廣泛的作為推薦系統的基礎，但不同於一般消費決策，醫療決策具有高度專業性，因此以醫院口碑為基礎的推薦系統少有人探討。故本研究目的為建立一套適用於評估醫療院所口碑的推薦系統。
　　本研究利用以內容為基礎的推薦系統做為主要的研究方法，由於醫療服務的推薦不同於產品推薦具有一定的規則，因此在口碑分析的部份利用建立控制字彙並透過問卷調查給予各詞彙分數的方式對口碑進行分析。本研究蒐集了台灣使用率最高的三個論壇網站（Mobile01、Ptt實業坊與Yahoo!奇摩知識+）共5,124筆口碑，建構一套牙醫推薦系統。
　　為了解本推薦系統的實用性，本研究利用個案研究法將本系統和Google搜尋引擎進行比較，分別評估兩者的搜尋時間、系統品質、系統效能、系統觀感和使用者行為意向五個部份。經由202位使用者實際操作之實驗結果得知，本系統能夠有效減少搜尋醫院資訊上的時間，且在系統品質、推薦的影響程度上都有不錯的水準。換言之，使用理性決策模式將詞彙進行分類，並依據大眾的觀感給予詞彙分數所建立出來的控制字彙，可以有效的提升醫療院所的推薦滿意程度。

摘要(英)

Online word of mouth (WOM) has been shown to be one of the most important sources of information for healthcare decisions. However, explosively growing information on the internet makes it difficult for consumers to effectively identify and appraise relevant WOMs. To provide a solution, this study proposed a novel personalized recommender system using text mining techniques, namely Hosearch. A total of 5,124 WOMs were collected from the selected public online forums in Taiwan, and the data were then used to develop the Hosearch recommender system. The empirical evaluations reveal that the proposed system is useful in associating the recommended items with user’s preferences more effectively than common search engines (e.g., Google).

關鍵字(中)

★ 推薦系統
★ 網路口碑
★ 語意分析
★ 資訊檢索
★ 牙醫

關鍵字(英)

★ Recommender System
★ Online Word of Mouth
★ Semantic Differential
★ Information Retrieval
★ Dentist

論文目次

一、緒論 1
1-1 研究背景 1
1-2 研究動機 2
1-3 研究目的 3
1-4 研究方法 3
1-5 研究範圍與限制 4
1-6 論文架構 4
二、文獻探討 6
2-1 口碑 6
2-2 健康資訊搜尋行為 7
2-3 推薦系統 10
2-3-1 以口碑為基礎的推薦系統 11
2-4 民眾選擇醫院考量因素 14
2-5 小結 18
三、研究方法 19
3-1 研究架構 19
3-2 研究範圍 21
3-3 建立控制字彙 22
3-4 口碑文章蒐集 24
3-5 口碑文章分析 25
3-6 個人化推薦機制 31
3-7 模型評估 33
3-7-1 實驗設計 33
3-7-2 問卷設計 34
3-8 小結 35
四、結果與討論 36
4-1 系統介紹 36
4-2 系統評估 40
4-2-1 搜尋時間 40
4-2-2 系統品質 41
4-2-3 系統效能 42
4-2-4 系統觀感 43
4-2-5 使用者行為意向 44
4-3 小結 46
五、結論與建議 47
5-1 研究發現 47
5-2 研究貢獻 48
5-3 研究限制與未來方向 49
參考文獻 51
附錄一 56
附錄二 65
附錄三 70

參考文獻

英文文獻
［1］ Aciar, S., Zhang, D., Simoff, S., & Debenham, J. (2007). Informed recommender: Basing recommendations on consumer product reviews. Intelligent Systems, IEEE, 22(3), 39-47.
［2］ Aljukhadar, M., Senecal, S., & Daoust, C.-E. (2012). Using recommendation agents to cope with information overload. International Journal of Electronic Commerce, 17(2), 41-70.
［3］ Arndt, J. (1967). Role of product-related conversations in the diffusion of a new product. Journal of marketing Research, 291-295.
［4］ Barsevick, A. M., & Johnson, J. E. (1990). Preference for information and involvement, information seeking and emotional responses of women undergoing colposcopy. Research in nursing & health, 13(1), 1-7.
［5］ Beresford, B. A., & Sloper, P. (2003). Chronically ill adolescents’ experiences of communicating with doctors: a qualitative study. Journal of Adolescent Health, 33(3), 172-179.
［6］ Cacheda, F., & Vina, A. (2001). Understanding how people use search engines: a statistical analysis for e-business. Paper presented at the Proceedings of the e-Business and e-Work Conference and Exhibition.
［7］ Cheung, C. M., & Lee, M. K. (2012). What drives consumers to spread electronic word of mouth in online consumer-opinion platforms. Decision Support Systems, 53(1), 218-225.
［8］ Chu, C.-H., & Wu, S.-H. (2013). A Chinese Restaurant Recommendation System Based on Mobile Context-Aware Services. 116-118.
［9］ Cline, R. J. W., & Haynes, K. M. (2001). Consumer health information seeking on the Internet the state of the art. HEALTH EDUCATION RESEARCH, 16, 671-692.
［10］Crane, F., & Lynch, J. (1988). Consumer selection of physicians and dentists: an examination of choice criteria and cue usage. Journal of Health Care Marketing, 8(3), 16-19.
［11］Dai, C., Qian, F., Jiang, W., Wang, Z., & Wu, Z. (2014). A Personalized Recommendation System for NetEase Dating Site. Proceedings of the VLDB Endowment, 7(13).
［12］Dave, K., Lawrence, S., & Pennock, D. M. (2003). Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. Paper presented at the Proceedings of the 12th international conference on World Wide Web.
［13］Davison, B. J., Gleave, M. E., Goldenberg, S. L., Degner, L. F., Hoffart, D., & Berkowitz, J. (2002). Assessing information and decision preferences of men with prostate cancer and their partners. Cancer nursing, 25(1), 42-49.

［14］Day, G. S. (1971). Attitude change, media and word of mouth. Journal of Advertising Research, 11(6), 31-40.
［15］De Groot, I., Otten, W., Dijs-Elsinga, J., Smeets, H., Kievit, J., & Marang-van de Mheen, P. (2012). Choosing between Hospitals The Influence of the Experiences of Other Patients. Medical Decision Making, 32(6), 764-778.
［16］Desrosiers, C., & Karypis, G. (2011). A Comprehensive Survey of Neighborhood-based Recommendation Methods. Recommender System Handbook, 107-144.
［17］Domingues, M. A., Gouyon, F., Jorge, A. M., Leal, J. P., Vinagre, J., Lemos, L., & Sordo, M. (2012). Combining usage and content in an online recommendation system for music in the Long Tail. International Journal of Multimedia Information Retrieval, 2(1), 3-13.
［18］Ekstrand, M. D., Riedl, J. T., & Konstan, J. A. (2011). Collaborative Filtering Recommender Systems. Foundations and Trends in Human-Computer Interaction, 4(2), 81-173.
［19］Ferguson, R. J., Paulin, M., & Bergeron, J. (2010). Customer sociability and the total service experience: antecedents of positive word-of-mouth intentions. Journal of Service Management, 21(1), 25-44.
［20］Fisher, C. M., & Anderson, C. J. (1990). Hospital advertising: does it influence consumers? Journal of Health Care Marketing, 10(4), 40-46.
［21］Gelb, B. D., & Sundaram, S. (2002). Adapting to “word of mouse”. Business Horizons, 45(4), 21-25.
［22］Gray, A. J. G., Gray, N., & Ounis, I. (2009). Searching and exploring controlled vocabularies. ACM, 1-5.
［23］Hashimoto, H., & Fukuhara, S. (2004). The influence of locus of control on preferences for information and decision making. Patient Educ Couns, 55(2), 236-240.
［24］Hennig‐Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word‐of‐mouth via consumer‐opinion platforms: what motivates consumers to articulate themselves on the internet? Journal of interactive marketing, 18(1), 38-52.
［25］Huang, S.-W., Wei, C.-C., & Lai, J.-L. (2011). A descriptive research of the first-time patients’ practical experience and expectations toward medical service. AIT.
［26］Jansen, B. J., Zhang, M., Sobel, K., & Chowdury, A. (2009). Micro-blogging as online word of mouth branding. ACM, 3859-3864.
［27］Javalgi, R. G., Rao, S., & Thomas, E. G. (1991). Choosing a hospital: analysis of consumer tradeoffs. Journal of Health Care Marketing, 11(1), 12-22.
［28］Johnson, J. D., & Johnson, D. J. (1997). Cancer-related information seeking: Hampton Press Cresskill, NJ.
［29］Kim, Y.-S., Oh, J.-S., Lee, J.-Y., & Chang, J.-H. (2005). An intelligent grading system for descriptive examination papers based on probabilistic latent semantic analysis. Lecture Notes in Computer Science, 3339, 1141-1146.
［30］Lambert, S. D., & Loiselle, C. G. (2007). Health information seeking behavior. Qual Health Res, 17(8), 1006-1019.
［31］Lane, P. M., & Lindquist, J. D. (1988). Hospital choice: a summary of the key empirical and hypothetical findings of the 1980s. Journal of Health Care Marketing, 8(4), 5-20.
［32］Lenz, E. R. (1984). Information seeking: A component of client decisions and health behavior. Advances in Nursing Science, 6(3), 59-72.
［33］Lops, P., de Gemmis, M., & Semeraro, G. (2011). Content-based Recommender Systems: State of the Art and Trends. Recommender System Handbook, 73-105.
［34］M., V., MS, C., & ARNP-C. (1998). Beyond Knowledge Deficit to a Proposal for Information‐Seeking Behaviors. International Journal of Nursing Terminologies and Classifications, 9(2), 129-135.
［35］Marang-van de Mheen, P., Dijs-Elsinga, J., Otten, W., Versluijs, M., Smeets, H., Van der Made, W., Kievit, J. (2010). The importance of experienced adverse outcomes on patients′ future choice of a hospital for surgery. Quality and Safety in Health Care, 19(6), e16-e16.
［36］McNee, S. M., Lam, S. K., Konstan, J. A., & Riedl, J. (2003). Interfaces for eliciting new user preferences in recommender systems User Modeling 2003 (pp. 178-187): Springer.
［37］Miao, Q., Li, Q., & Dai, R. (2009). AMAZING: A sentiment mining and retrieval system. Expert Systems with Applications, 36(3), 7192-7198.
［38］Molem, V. D. (1999). Relating information needs to the cancer experience: 1 Information as a key coping strategy. European Journal of Cancer Care, 8(4), 238-244.
［39］Murray, K. B., & Schlacter, J. L. (1990). The impact of services versus goods on consumers’ assessment of perceived risk and variability. Journal of the Academy of Marketing Science, 18(1), 51-65.
［40］Pazzani, M. J., & Billsus, D. (2007). Content-based Recommendation Systems. Lecture Notes in Computer Science, 4321, 325-341.
［41］Pu, P., & Chen, L. (2006). Trust building with explanation interfaces. Paper presented at the Proceedings of the 11th international conference on Intelligent user interfaces.
［42］Pu, P., Chen, L., & Hu, R. (2010). A User-Centric Evaluation Framework for Recommender Systems.
［43］Pu, P., Chen, L., & Hu, R. (2012). Evaluating recommender systems from the user’s perspective: survey of the state of the art. User Modeling and User-Adapted Interaction, 22(4-5), 317-355.
［44］Rees, C. E., & Bath, P. A. (2000). The psychometric properties of the Miller Behavioural Style Scale with adult daughters of women with early breast cancer: a literature review and empirical study. Journal of Advanced Nursing, 32(2), 366-374.
［45］Rees, C. E., & Bath, P. A. (2001). Information-seeking behaviors of women with breast cancer. Paper presented at the Oncology nursing forum.
［46］Resnick, P., Kuwabara, K., Zeckhauser, R., & Friedman, E. (2000). Reputation systems. ACM, 43(12), 45-48.
［47］Resnick, P., & Varian, H. R. (1997). Recommender systems. ACM, 40(3), 56-58.
［48］Salton, G., & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Information processing & management, 24(5), 513-523.
［49］Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2000). Analysis of Recommendation Algorithms for E-Commerce. ACM, 158-167.
［50］Shiloh, S., Ben-Sinai, R., & Keinan, G. (1999). Effects of Controllability, Predictability, and Information-Seeking Style on Interest in Predictive Genetic Testing. Personality and Social Psychology Bulletin, 25(10), 1187-1195.
［51］Stratmann, W. C. (1975). A study of consumer attitudes about health care: the delivery of ambulatory services. Medical care, 537-548.
［52］Szomszor, M., Cattuto, C., Alani, H., O′Hara, K., Baldassarri, A., Loreto, V., & Servedio, V. D. P. (2007). Folksonomies, the semantic web, and movie recommendation. Proceedings of the Workshop on Bridging the Gap between Semantic Web and Web 2.0 at the 4th European Semantic Web Conference,, 86-91.
［53］Szwajcer, E. M., Hiddink, G. J., Koelen, M. A., & van Woerkum, C. M. (2005). Nutrition-related information-seeking behaviours before and throughout the course of pregnancy: consequences for nutrition communication. Eur J Clin Nutr, 59 Suppl 1, S57-65.
［54］Taraghi, B., Grossegger, M., Ebner, M., & Holzinger, A. (2013). Web analytics of user path tracing and a novel algorithm for generating recommendations in Open Journal Systems. Online Information Review, 37(5), 672-691.
［55］Tengilimoglu, D., Yesiltas, M., Kisa, A., & Dziegielewski, S. F. (2008). The role of public relations activities in hospital choice. Health marketing quarterly, 24(3-4), 19-31.
［56］Warner, D., & Procaccino, J. D. (2004). Toward wellness: Women seeking health information. Journal of the American Society for Information Science and Technology, 55(8), 709-730.
［57］Wattenbarger, D. W., Bailey, J. A., & Martinez, S. J. (1977). Interactive system for controlled vocabulary maintenance. ACM, 79-85.
［58］Wensing, M., & Elwyn, G. (2002). Research on patients views in the evaluation and improvement of quality of care. Qual Saf Health Care, 11, 153-157.
［59］Yan, Z., Xing, M., Zhang, D., & Ma, B. (2015). EXPRS: An extended pagerank method for product feature extraction from online consumer reviews. Information & Management.
中文文獻
［1］江淑娜，「連鎖式中醫診所服務品質關鍵因素之分析」，中華大學企業管理學系，碩士論文，2011年。
［2］李佳曄，「以網路口碑之語意萃取為基礎的推薦系統」，中原大學資訊管理研究所，碩士論文，2008年。
［3］杜慶山，「以線上口碑萃取為基礎之消費推薦系統」，中原大學資訊管理研究所，碩士論文，2010年。
［4］林政輝，「以口碑為基礎之人化餐廳推薦機制」，中原大學資訊管理研究所，碩士論文，2010年。
［5］時立哲，「使用模糊本體開發餐廳口碑的推薦系統」，中原大學資訊管理研究所，碩士論文，2013年。
［6］郭怡辰，「糖尿病患者就醫選擇因素探討-以桃園縣龜山鄉為例」，台北醫學大學醫務管理學研究所，碩士論文，2010年。
［7］陳德美，「發展語意感知模型於網路口碑推薦」，中原大學資訊管理研究所，碩士論文，2009年。
［8］彭晴憶，「醫療口碑內涵初探－以台北市兩家皮膚科診所為例」，國立臺灣大學衛生政策與管理研究所，碩士論文，2010年。
［9］蔡政峰，「高雄市牙醫師與病患對人工植牙醫療品質認知之研究」，國立中山大學管理學院高階經營碩士學程在職專班，碩士論文.
［10］鄭碧薇，「社區民眾就醫需求相關因素及滿意度探討-以桃園某區域醫院為例」，長庚大學商管專業學院學碩士位學程在職專班醫務管理組，碩士論文，2014年。
［11］iThome。2008年，取自 http://www.ithome.com.tw/node/50112。
［12］台灣衛生福利部中央建康保險署：健保特約醫療院所名冊。2014年，取自 http://www.nhi.gov.tw/webdata/webdata.aspx?menu=17&menu_id=879&WD_ID=994&webdata_id=934。
［13］財團法人資訊工業策進會。2014年，取自http://www.iii.org.tw/(X(1)S(w2wjiteh5j131eyz3eji5m3g))/m/ICT-more.aspx?id=770。
［14］資策會。2014年，取自 http://www.find.org.tw/market_info.aspx?n_ID=7208。
［15］資策會產業情報研究所。2014年，取自http://mic.iii.org.tw/intelligence/pressroom/pop_pressfull.asp?sno=366&type1=2。

指導教授

許文錦(Wen-chin Hsu)

審核日期

2015-7-13

推文