博碩士論文 100481025 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:22 、訪客IP:18.227.48.141
姓名 鄭雲珊(Yun-Shan Cheng)  查詢紙本館藏   畢業系所 企業管理學系
論文名稱 建構以價值為基礎的推薦方法
(Identifying and Recommending User-Interested Attributes with Values)
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摘要(中) 為了吸引線上消費者的注意力以及增加其購買意願,許多線上電子商務業者紛紛採用以內容為基礎的推薦方法作為其線上購物之推薦系統。然而,除了以文字為基礎的文件之外,很少理論深入探討如何有效的篩選消費者感興趣的產品特徵。然而,根據方法目的鏈理論—消費者選擇產品的關鍵在於其「屬性/利益/價值」。因此,本研究研發一個建構於方法目的鏈理論上的演算法,用來識別出消費者偏好的產品屬性並進一步加以推薦。本研究測試兩組實驗,用以比較本研究所研發之演算法『以價值為基礎的推薦方法』(Value-Based Recommendation, VBR)與以內容為基礎的推薦方法以及混合式的推薦方法做精確度與效能之比較。
摘要(英) To retain consumer attention and increase their purchasing rates, many online e-commerce vendors have adopted content-based approaches in their recommender systems. However, except text based documents, there are few theoretic background guiding the selection of elements. On the other hand, Means-End Chain theory pointed out that deciding elements that dictate product selection include attributes, benefits, and values can be systematically identified. This study strived to establish a methodology to recommend favorite attributes to users based on Means-End Chain theory. Two experiments were conducted to compare and contrast the performance of the proposed method Value-Based Recommendation (VBR) and two traditional content (attribute) based methodologies.
關鍵字(中) ★ 使用者價值
★ 推薦系統
★ 方法目的鏈
關鍵字(英) ★ User values
★ recommendation system
★ Means end chain
論文目次 中文提要 ……………………………………………………………… i
英文提要 ……………………………………………………………… ii
目錄 ……………………………………………………………… iii
圖目錄 ……………………………………………………………… iv


一、 緒論………………………………………………………… 1
二、 文獻探討…………………………………………………… 5
2-1 方法目的鏈理論…………………………………………… 6
2-2 階梯法……………………………………………………… 8
2-3 以內容為基礎的推薦系統與相關議題…………………… 10
2-3-1 過度專業化………………………………………………… 10
2-3-2 受限制的內容分析問題…………………………………… 11
三、 研究方法…………………………………………………… 13
3-1 以軟式與硬式階梯法建構價值階層圖…………………… 13
3-2 以價值階層圖為基礎之以價值為基礎的推薦方法……… 14
四、 結果………………………………………………………… 18
4-1 經由軟式階梯法來發展硬式階梯問項…………………… 18
4-2 以硬式階梯法建構價值為基礎的推薦方法……………… 19
4-3 比較方法說明……………………………………………… 21
4-4 推薦精確度之比較:以價值為基礎的推薦方法對以內容為基礎的推薦方法與混合式推薦方法 22
4-5 驗證以機率增強之價值階層圖的適用性 23
五、 結論………………………………………………………… 24
5-1 結論與意涵………………………………………………… 24
5-2 貢獻和未來研究方向……………………………………… 25
參考文獻 ……………………………………………………………… 28
參考文獻 Adomavicius, G. and Tuzhilin, A. (2005), "Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions", IEEE Transactions on Knowledge and Data Engineering, Vol. 17 No. 6, pp. 734-749.

Ares, G., Gimenez, A. and Gambaro, A. (2008), "Understanding consumers’ perception of conventional and functional yogurts using word association and hard laddering", Food Quality and Preference, Vol. 19 No. 7, pp. 636-643.

ARO. (2013), "Google+ statistics directory", available at: http://www.insightxplorer.com/news/news_05_22_13.html (accessed 13 June 2016).
Bach, N.X., Hai, N.D. and Phuong, T.M. (2016), "Personalized recommendation of stories for commenting in forum-based social media", Information Sciences, Vol. 352–353, pp. 48-60.

Balabanovi?, M. and Shoham, Y. (1997), "Fab: content-based, collaborative recommendation", Communications of the ACM, Vol. 40 No. 3, pp. 66-72.

Billsus, D. and Pazzani, M.J. (2000), "User modeling for adaptive news access", User Modeling and User-Adapted Interaction, Vol. 10 No. 2-3, pp. 147-180.

Blanco-Fernandez, Y., Lopez-Nores, M., Gil-Solla, A., Ramos-Cabrer, M. and Pazos-Arias, J.J. (2011), "Exploring synergies between content-based filtering and spreading activation techniques in knowledge-based recommender systems", Information Sciences, Vol. 181 No. 21, pp. 4823-4846.

Bloemer, J. and Dekker, D. (2007), "Effects of personal values on customer satisfaction: an empirical test of the value percept disparity model and the value disconfirmation model", International Journal of Bank Marketing, Vol. 25 No. 5, pp. 276-291.

Bobadilla, J., Ortega, F., Hernando, A. and Gutierrez, A. (2013), "Recommender systems survey", Knowledge-Based Systems, Vol. 46, pp. 109-132.

Bojnordi, E. and Moradi, P. (2012), “A novel collaborative filtering model based on combination of correlation method with matrix completion technique”, in The 16th CSI international symposium on artificial intelligence and signal processing (AISP 2012), IEEE, Shiraz, Fars, pp. 191-194.

Botschen, G., Thelen, E.M. and Pieters, R. (1999), "Using means?end structures for benefit segmentation: an application to services", European Journal of Marketing, Vol. 33 No. 1/2, pp. 38-58.

Brandtzag, P.B. and Heim, J. (2009), "Why people use social networking sites", in Ozok, A.A. and Zaphiris, P. (Eds.), Online Communities and Social Computing, Springer, Berlin, Heidelberg, pp. 143-152.

Browning, G., Halcli, A., and Webster, F. (1999), Understanding contemporary society: Theories of the present, Sage, Thousand Oaks, CA.

Burke, R. (2002), "Hybrid recommender systems: survey and experiments", User Modeling and User-Adapted Interaction, Vol. 12 No. 4, pp. 331-370.

Chang, Y.P. and Zhu, D.H. (2011), "Understanding social networking sites adoption in China: a comparison of pre-adoption and post-adoption", Computers in Human Behavior, Vol. 27 No. 5, pp. 1840-1848.

Check Facebook. (2013), "Facebook statistics directory", available at: http://www.socialbakers.com/statistics/facebook/ (accessed 13 January 2016).

Chen, Y.-C., Shang, R.-A. and Li, M.-J. (2014), "The effects of perceived relevance of travel blogs’ content on the behavioral intention to visit a tourist destination", Computers in Human Behavior, Vol. 30, pp. 787-799.

Claypool, M., Gokhale, A., Miranda, T., Murnikov, P., Netes, D. and Sartin, M. (1999), “Combining content-based and collaborative filters in an online newspaper”, in Proceedings of ACM SIGIR workshop on recommender systems, Berkeley, CA, USA, Vol. 60, pp. 1-11.

Davis, F.D. (1989), "Perceived usefulness, perceived ease of use, and user acceptance of information technology", MIS Quarterly, Vol. 13 No. 3, pp. 319-340.

De Campos, L.M., Fernandez-Luna, J.M., Huete, J.F. and Rueda-Morales, M.A. (2010), "Combining content-based and collaborative recommendations: a hybrid approach based on Bayesian networks", International Journal of Approximate Reasoning, Vol. 51 No. 7, pp. 785-799.

Du, Z., Zhang, T., Chen, Y., Ai, L. and Wang, X. (2011), "A content and user-oblivious video-recommendation algorithm", Simulation Modelling Practice and Theory, Vol. 19 No. 9, pp. 1895-1912.

Feunekes, G.I.J. and Den Hoed, W. (2001), "Quantifying consumers’ motivational strutures for food products-the association pattern technique", in Excellence in Internal Research, The World Association of Research Professionals, Amsterdam, Netherlands. pp. 1-15.

Gengler, C.E., Klenosky, D.B. and Mulvey, M.S. (1995), "Improving the graphic representation of means-end results", International Journal of Research in Marketing, Vol. 12 No. 3, pp. 245-256.

Goldenberg, M.A., Klenosky, D., TO′Leary, J. and Templin, T.J. (2000), "A means-end investigation of ropes course experiences", Journal of Leisure Research, Vol. 32 No. 2, pp. 208-224.

Grunert, K.G. and Grunert, S.C. (1995), "Measuring subjective meaning structures by the laddering method: theoretical considerations and methodological problems", International Journal of Research in Marketing, Vol. 12 No. 3, pp. 209-225.

Guenzi, P. and Troilo, G. (2006), "Developing marketing capabilities for customer value creation through marketing-sales integration", Industrial Marketing Management, Vol. 35 No. 8, pp. 974-988.

Gulnar, B., Balc?, ?. and Cak?r, V. (2010), "Motivations of Facebook, You Tube and similar web sites users", Bilig Vol. 54, pp. 161–184.

Guo, Y., Wang, M. and Li, X. (2017), "Application of an improved Apriori algorithm in a mobile e-commerce recommendation system", Industrial Management & Data Systems, Vol. 117 No. 2, pp. 287-303.

Gutman, J. (1982), "A means-end chain model based on consumer categorization processes", Journal of Marketing, Vol. 46 No. 2, pp. 60-72.

Gutman, J. (1997), "Means-end chains as goal hierarchies", Psychology and Marketing, Vol. 14 No. 6, pp. 545-560.

Haley, R.I. (1968), "Benefit segmentation: a decision-oriented research tool", Journal of Marketing, Vol. 32 No. 3, pp. 30-35.

He, C., Parra, D. and Verbert, K. (2016), "Interactive recommender systems: a survey of the state of the art and future research challenges and opportunities", Expert Systems with Applications, Vol. 56, pp. 9-27.

Henneberg, S.C., Gruber, T., Reppel, A., Ashnai, B. and Naude, P. (2009), "Complaint management expectations: an online laddering analysis of small versus large firms", Industrial Marketing Management, Vol. 38 No. 6, pp. 584-598.

Hofstede, G. (1998), "Attitudes, values and organizational culture: disentangling the concepts", Organization Studies, Vol. 19 No. 3, pp. 477-493.

Horeni, O., Arentze, T.A., Dellaert, B.G.C. and Timmermans, H.J.P. (2014), "Online measurement of mental representations of complex spatial decision problems: comparison of CNET and hard laddering", Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 22, pp. 170-183.

Hsieh, H.F., and Shannon, S.E. (2005), "Three approaches to qualitative content analysis", Qualitative health research, Vol. 15 No. 9, pp. 1277-1288.

Hsu, M.-H., Chang, C.-M. and Chuang, L.-W. (2015), "Understanding the determinants of online repeat purchase intention and moderating role of habit: the case of online group-buying in Taiwan", International Journal of Information Management, Vol. 35 No. 1, pp. 45-56.

Hsu, M.-H., Chang, C.-M., Chu, K.-K. and Lee, Y.-J. (2014), "Determinants of repurchase intention in online group-buying: the perspectives of DeLone & McLean IS success model and trust", Computers in Human Behavior, Vol. 36, pp. 234-245.

Javari, A. and Jalili, M. (2014), "Cluster-based collaborative filtering for sign prediction in social networks with positive and negative links", ACM Transactions on Intelligent Systems and Technology (TIST), Vol. 5 No. 2, pp. 24.

Joachims, T., Freitag, D. and Mitchell, T.M. (1997), “Web watcher: a tour guide for the world wide web”, in International joint conference on artificial intelligence, IJCAI, Nagoya, Vol. 1, pp. 770-777.

Jung, T., Youn, H. and McClung, S. (2007), "Motivations and self-presentation strategies on Korean-based "Cyworld" weblog format personal homepages", Cyber Psychology & Behavior, Vol. 10 No. 1, pp. 24-31.

Jung, Y. and Kang, H. (2010), "User goals in social virtual worlds: a means-end chain approach", Computers in Human Behavior, Vol. 26 No. 2, pp. 218-225.

Kaapu, T. and Tiainen, T. (2009), "Consumers′ views on privacy in e-commerce", Scandinavian Journal of Information Systems, Vol. 21 No. 1, pp. 1-20.

Kassarjian, H.H. (1977), "Content analysis in consumer research", Journal of Consumer Research, Vol. 4 No. 1, pp. 8-18.

Keng, K.A., Jung, K., Jiuan, T.S. and Wirtz, J. (2000), "The influence of materialistic inclination on values, life satisfaction and aspirations: an empirical analysis", Social Indicators Research, Vol. 49 No. 3, pp. 317-333.

Kim, C., Mirusmonov, M. and Lee, I. (2010), "An empirical examination of factors influencing the intention to use mobile payment", Computers in Human Behavior, Vol. 26 No. 3, pp. 310-322.

Kim, H.S. (2005), "Consumer profiles of apparel product involvement and values", Journal of Fashion Marketing and Management: An International Journal, Vol. 9 No. 2, pp. 207-220.

Kim, H.-W., Gupta, S. and Koh, J. (2011a), "Investigating the intention to purchase digital items in social networking communities: a customer value perspective", Information & Management, Vol. 48 No. 6, pp. 228-234.

Kim, Y., Sohn, D. and Choi, S.M. (2011b), "Cultural difference in motivations for using social network sites: a comparative study of American and Korean college students", Computers in Human Behavior, Vol. 27 No. 1, pp. 365-372.

Klenosky, D.B. (2002), "The “pull” of tourism destinations: a means-end investigation", Journal of Travel Research, Vol. 40 No. 4, pp. 396-403.

Krippendorff, K. (2012), Content Analysis: An Introduction to Its Methodology, Sage, Thousand Oaks, CA.

Lee, S., Choi, K., & Suh, Y. (2013), "A personalized trustworthy seller recommendation in an open market", Expert Systems with Applications, Vol. 40 No. 4, pp. 1352-1357.

Lee, H., Choi, J., Kim, K.K. and Lee, A.R. (2014), "Impact of anonymity on information sharing through internal psychological processes: a case of South Korean online communities", Journal of Global Information Management (JGIM), Vol. 22 No. 3, pp. 57-77.

Lee, W.-I., Chang, C.-Y. and Liu, Y.-L. (2010), "Exploring customers’ store loyalty using the means-end chain approach", Journal of Retailing and Consumer Services, Vol. 17 No. 5, pp. 395-405.

Leisen, B. (2001), "Image segmentation: the case of a tourism destination", Journal of Services Marketing, Vol. 15 No. 1, pp. 49-66.

Lin, L.-Z. and Yeh, H.-R. (2013), "A means-end chain of fuzzy conceptualization to elicit consumer perception in store image", International Journal of Hospitality Management, Vol. 33, pp. 376-388.

Lin, Y.-L. and Lin, H.-W. (2011), "A study on the goal value for massively multiplayer online role-playing games players", Computers in Human Behavior, Vol. 27 No. 6, pp. 2153-2160.

Lind, L.W. (2007), "Consumer involvement and perceived differentiation of different kinds of pork-a means-end chain analysis", Food Quality and Preference, Vol. 18 No. 4, pp. 690-700.

Liu, D.-R., Omar, H., Liou, C.-H., Chi, H.-C. and Hsu, C.-H. (2015), "Recommending blog articles based on popular event trend analysis", Information Sciences, Vol. 305, pp. 302-319.

Lopez-Nores, M., Blanco-Fernandez, Y., Pazos-Arias, J.J. and Gil-Solla, A. (2012), "Property-based collaborative filtering for health-aware recommender systems", Expert Systems with Applications, Vol. 39 No. 8, pp. 7451-7457.

Lops, P., de Gemmis, M. and Semeraro, G. (2011), "Content-based recommender systems: state of the art and trends", in Ricci, F., Rokach, L., Shapira, B. and Kantor, P.B. (Eds.), Recommender Systems Handbook, Springer US, Boston, MA, pp. 73-105.

Majid, A., Chen, L., Chen, G., Mirza, H.T., Hussain, I. and Woodward, J. (2013), "A context-aware personalized travel recommendation system based on geotagged social media data mining", International Journal of Geographical Information Science, Vol. 27 No. 4, pp. 662-684.

Maslow, A. H. (1943), "A theory of human motivation". Psychological review, Vol. 50 No. 4, pp. 370-396.

Middleton, S.E., Roure, D.D. and Shadbolt, N.R. (2009), "Ontology-based recommender systems", in Staab, S. and Studer, R. (Eds.), Handbook on Ontologies, Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 779-796.

Mitchell, A. (1983), The Nine American Lifestyles: Who We Are and Where We’re Going, Scribner Book Company, New York, NY.

Moghimi, V., Jusan, M.B.M. and Izadpanahi, P. (2016), "Iranian household values and perception with respect to housing attributes", Habitat International, Vol. 56, pp. 74-83.

Mooney, R.J. and Roy, L. 2000. “Content-based book recommending using learning for text categorization”, in Proceedings of the fifth ACM conference on digital libraries, ACM, San Antonio, Texas, USA, pp. 195-204.

Mulvey, M.S., Olson, J.C., Celsi, R.L. and Walker, B.A. (1994), "Exploring the relationships between means-end knowledge and involvement", in Allen, C.T. and John, D.R. (Eds.), NA-Advances in Consumer Research, Association for Consumer Research, Provo, UT, pp. 51-57.

Myers, J.H. (1976), "Benefit structure analysis: a new tool for product planning", Journal of Marketing, Vol. 40 No. 4, pp. 23-32.

Narducci, F., Basile, P., Musto, C., Lops, P., Caputo, A., de Gemmis, M., Iaquinta, L. and Semeraro, G. (2016), "Concept-based item representations for a cross-lingual content-based recommendation process", Information Sciences, Vol. 374, pp. 15-31.

Ngai, E.W.T., Moon, K.L.K., Lam, S.S., Chin, E.S.K. and Tao, S.S.C. (2015), "Social media models, technologies, and applications: an academic review and case study", Industrial Management & Data Systems, Vol. 115 No. 5, pp. 769-802.

Olson, J.C. (1988), “Theoretical foundations of means-end chains”, Unpublished working paper series, number 174, Penn State University, State College, College of Business Administration, 15 July.

Olson, J.C. and Reynolds, T.J. (1983), "Understanding consumers’ cognitive structures: implications for advertising strategy", Advertising and Consumer Psychology, Vol. 1, pp. 77-90.

Pazzani, M.J. and Billsus, D. (2007), "Content-based recommendation systems", in Brusilovsky, P., Kobsa, A. and Nejdl, W. (Eds.), The Adaptive Web: Methods and Strategies of Web Personalization, Springer, Berlin Heidelberg, pp. 325-341.

Pearson, K. (1895), "Note on regression and inheritance in the case of two parents", Proceedings of the Royal Society of London, Vol. 58, pp. 240-242.

Perreault, W.D. and Leigh, L.E. (1989), "Reliability of nominal data based on qualitative judgments", Journal of Marketing Research, Vol. 26 No. 2, pp. 135-148.

Phillips, J.M. and Reynolds, T.J. (2009), "A hard look at hard laddering: a comparison of studies examining the hierarchical structure of means?end theory", Qualitative Market Research: An International Journal, Vol. 12 No. 1, pp. 83-99.

Pieters, R., Baumgartner, H. and Allen, D. (1995), "A means-end chain approach to consumer goal structures", International Journal of Research in Marketing, Vol. 12 No. 3, pp. 227-244.

Protasiewicz, J., Pedrycz, W., Koz?owski, M., Dadas, S., Stanis?awek, T., Kopacz, A. and Ga???ewska, M. (2016), "A recommender system of reviewers and experts in reviewing problems", Knowledge-Based Systems, Vol. 106, pp. 164-178.

Puglisi, S., Parra-Arnau, J., Forne, J. and Rebollo-Monedero, D. (2015), "On content-based recommendation and user privacy in social-tagging systems", Computer Standards & Interfaces, Vol. 41, pp. 17-27.

Reppel, A.E., Szmigin, I. and Gruber, T. (2006), "The iPod phenomenon: identifying a market leader′s secrets through qualitative marketing research", Journal of Product & Brand Management, Vol. 15 No. 4, pp. 239-249.

Reynolds, T.J. and Gutman, J. (1988), "Laddering theory, method, analysis, and interpretation", Journal of Advertising Research, Vol. 28 No. 1, pp. 11-31.

Reynolds, T.J. and Olson, J.C. (2001), Understanding Consumer Decision Making: The Means-end Approach to Marketing and Advertising Strategy, Psychology Press, New Jersey.

Rokeach, M. (1973), The Nature of Human Values, Free Press, New York, NY.

Russell, C.G., Flight, I., Leppard, P., van Lawick van Pabst, J.A., Syrette, J.A. and Cox, D.N. (2004), "A comparison of paper-and-pencil and computerised methods of “hard” laddering", Food Quality and Preference, Vol. 15 No. 3, pp. 279-291.

Ryan, R.M. and Deci, E.L. (2000), "Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being", American psychologist, Vol. 55 No. 1, pp. 68-78.

Santosa, M. and Guinard, J.-X. (2011), "Means-end chains analysis of extra virgin olive oil purchase and consumption behavior", Food Quality and Preference, Vol. 22 No. 3, pp. 304-316.

Schaefer, C.D. (2008), “Motivations and usage patterns on social network sites”, in European conference on information systems, AISeL, Karlsruhe, pp. 2088-2099.

Sheldon, P. (2008), "The relationship between unwillingness-to-communicate and students′ facebook use", Journal of Media Psychology: Theories, Methods, and Applications, Vol. 20 No. 2, pp. 67-75.

Shih, D.-H., Yen, D.C., Lin, H.-C. and Shih, M.-H. (2011), "An implementation and evaluation of recommender systems for traveling abroad", Expert Systems with Applications, Vol. 38 No. 12, pp. 15344-15355.

Shih, T.K., Chiu, C.F., Hsu, H.H. and Lin, F. (2002), "An integrated framework for recommendation systems in e?commerce", Industrial Management & Data Systems, Vol. 102 No. 8, pp. 417-431.

Special, W.P. and Li-Barber, K.T. (2012), "Self-disclosure and student satisfaction with facebook", Computers in Human Behavior, Vol. 28 No. 2, pp. 624-630.

Ter Hofstede, F., Audenaert, A., Steenkamp, J.B.E.M. and Wedel, M. (1998), "An investigation into the association pattern technique as a quantitative approach to measuring means-end chains", International Journal of Research in Marketing, Vol. 15 No. 1, pp. 37-50.

Valette-Florence, P., Sirieix, L., Grunert, K. and Nielsen, N. (2000), "Means-end chain analyses of fish consumption in Denmark and France: a multidimensional perspective", Journal of Euromarketing, Vol. 8 No. 1-2, pp. 15-27.

Villamil-Gomez, W.E., Gonzalez-Camargo, O., Rodriguez-Ayubi, J., Zapata-Serpa, D. and Rodriguez-Morales, A.J. (2016), "Dengue, chikungunya and Zika co-infection in a patient from Colombia", Journal of Infection and Public Health, Vol. 9 No. 5, pp. 684-686.

Voss, R., Gruber, T. and Szmigin, I. (2007), "Service quality in higher education: the role of student expectations", Journal of Business Research, Vol. 60 No. 9, pp. 949-959.
Walker, B.A. and Olson, J.C. (1991), "Means-end chains: connecting products with self", Journal of Business Research, Vol. 22 No. 2, pp. 111-118.

Wang, Y., Stash, N., Aroyo, L., Gorgels, P., Rutledge, L. and Schreiber, G. (2008), "Recommendations based on semantically enriched museum collections", Web Semantics: Science, Services and Agents on the World Wide Web, Vol. 6 No. 4, pp. 283-290.

Wimmer, R.D. and Dominick, J.R. (2013), Mass Media Research, Cengage Learning, Boston, MA.

Young, S. and Feigin, B. (1975), "Using the benefit chain for improved strategy formulation", The Journal of Marketing, Vol. 39 No. 3, pp. 72-74.
指導教授 許秉瑜(Ping-Yu Hsu) 審核日期 2018-7-26
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