Výsledky vyhledávání - "淡江大學資訊管理學系碩士班"
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Témata: 隱私計算理論, 個人化服務, 感知資訊關聯, 資訊敏感度, 調節焦點, Information privacy, Personalized services, Privacy calculus, Relevance theory, Regulatory focus theory
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Relation: 一、 中文文獻：\n[1] 何自然，冉永平（2000)。《關聯性：溝通與認知》導讀。外語教學與研究出版社。取自https://doi.org/10.1191/026765800673158592\n[2] 賴立芸（2019）。資訊隱私悖論因素探討。國立政治大學資訊管理學系碩士論文，台北市。取自https://hdl.handle.net/11296/uzx2qt\n[3] 林承穎（2017）。從調節焦點和隱私計算探討社群網站使用者隱私揭露之研究。淡江大學資訊管理學系碩士班碩士論文，新北市。取自https://hdl.handle.net/11296/xaf922\n[4] 趙庭瑋（2009）。調節焦點對尋求多樣化之影響。國立臺灣大學商學研究所碩士論文，台北市。取自http://ntur.lib.ntu.edu.tw//handle/246246/184558\n[5] 馬慶玲（2010）。調節焦點影響廣告效果之研究。國立政治大學心理學研究所碩士論文，台北市。 取自https://hdl.handle.net/11296/uemup5\n\n二、 英文文獻：\n[1] Anderson, C. L., &Agarwal, R. (2011). The digitization of healthcare: Boundary risks, emotion, and consumer willingness to disclose personal health information. In Information Systems Research (Vol. 22, Issue 3, pp. 469–490). https://doi.org/10.1287/isre.1100.0335\n[2] Bansal, G., Zahedi, F. M., &Gefen, D. (2010). The impact of personal dispositions on information sensitivity, privacy concern and trust in disclosing health information online. Decision Support Systems, 49(2), 138–150. https://doi.org/10.1016/j.dss.2010.01.010\n[3] Basyuk, D., Prymak, T., &Pohuda, N. (2018). The role of informational technologies in creating a personalized customer experience: a case study of tourism branch in Ukraine. Centre for European Studies (CES) Working Papers, 10(3),406–422. http://search.ebscohost.com/login.aspx?direct=true&db=asx&AN=133272521&lang=de&site=eds-live\n[4] Brown, J. O., Broderick, A. J., &Lee, N. (2007). Online Communities : Conceptualizing the Online Social Network. Journal of Interactive Marketing, 21(3), 2–20. https://doi.org/10.1002/dir\n[5] Celsi, R. L., &Olson, J. C. (1988). The Role of Involvement in Attention and Comprehension Processes. Journal of Consumer Research, 15(2), 210. https://doi.org/10.1086/209158\n[6] Chellappa, R. K., &Raymond G. Sin. (2005). Personalization versus Privacy: An Empirical Examination of the Online Consumer’s Dilemma. Information Technology and Management, 6(2–3), 181–202. https://doi.org/10.3138/cras.42.1.7\n[7] Chellappa, R. K., &Shivendu, S. (2007). An economic model of privacy: A property rights approach to regulatory choices for online personalization. Journal of Management Information Systems, 24(3), 193–225. https://doi.org/10.2753/MIS0742-1222240307\n[8] Craciun, G. (2018). Choice defaults and social consensus effects on online information sharing: The moderating role of regulatory focus. Computers in Human Behavior, 88(June), 89–102. https://doi.org/10.1016/j.chb.2018.06.019\n[9] Culnan, M. J., Armstrong, P. K., Science, S. O., Feb, N. J., Culnan, M. J., &Armstrong, P. K. (1999). Information Privacy Concerns , Procedural Fairness , and Impersonal Trust : An Empirical Investigation. 10(1), 104–115.\n[10] Culnan, M. J., &Bies, R. J. (2003). Consumer privacy: Balancing economic and justice considerations. Journal of Social Issues, 59(2), 323–342. https://doi.org/10.1111/1540-4560.00067\n[11] Dienlin, T., &Metzger, M. J. (2016). An Extended Privacy Calculus Model for SNSs: Analyzing Self-Disclosure and Self-Withdrawal in a Representative U.S. Sample. Journal of Computer-Mediated Communication, 21(5), 368–383. https://doi.org/10.1111/jcc4.12163\n[12] Dinev, T., &Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80. https://doi.org/10.1287/isre.1060.0080\n[13] Dinev, T., Xu, H., Smith, J. H., &Hart, P. (2013). Information privacy and correlates: An empirical attempt to bridge and distinguish privacyrelated concepts. European Journal of Information Systems, 22(3), 295–316. https://doi.org/10.1057/ejis.2012.23\n[14] Gauzente, C. (2004). Web Merchants’ Privacy and Security Statements : How Reassuring Are They for Consumers ? a Two-Sided Approach. Journal of Electronic Commerce Research, 5(3), 181–198.\n[15] Gerber, N., Gerber, P., &Volkamer, M. (2018). Explaining the privacy paradox: A systematic review of literature investigating privacy attitude and behavior. Computers and Security, 77, 226–261. https://doi.org/10.1016/j.cose.2018.04.002\n[16] Gupta, Ashish; Patel, Vimla L.; Greenes, R. A. (2016). Advances in Healthcare Informatics an Analytics. https://doi.org/10.1007/978-3-319-23294-2\n[17] Higgins, E. T. (1998). Promotion and Prevention: Regulatory Focus as A Motivational Principle. Advances in Experimental Social Psychology, 30(C), 1–46. https://doi.org/10.1016/S0065-2601(08)60381-0\n[18] Hsiao, C. H., Tsai, C. F., &Hsu, Y. H. (2012). The influences of self-construal and regulatory focus on impulsive buying behavior. NTU Management Review, 23(1), 119–150. https://doi.org/10.6226/NTURM2012.AUG.M5\n[19] Jung, A. R. (2017). The influence of perceived ad relevance on social media advertising: An empirical examination of a mediating role of privacy concern. Computers in Human Behavior, 70, 303–309. https://doi.org/10.1016/j.chb.2017.01.008\n[20] Kehr, F., Kowatsch, T., Wentzel, D., &Fleisch, E. (2015). Blissfully ignorant: The effects of general privacy concerns, general institutional trust, and affect in the privacy calculus. Information Systems Journal, 25(6), 607–635. https://doi.org/10.1111/isj.12062\n[21] Krasnova, H., Spiekermann, S., Koroleva, K., &Hildebrand, T. (2010). Online Social Networks: Why We Disclose Author Version. Journal of Information Technology, 25(2), 109–125.\n[22] Krishnan, M. S., &Awad, N. F. (2006). The Personalization Privacy Paradox : An Empirical Evaluation of Information Transparency and the Willingness to be Profiled Online for Personalization. 30(1), 13–28.\n[23] Laufer, R. S., &Wolfe, M. (1977). Privacy as a concept and a social issue: A multidimensional developmental theory. Journal of Social Issues, 33(3), 22–42.\n[24] Li, H., &Sarathy, R. (2007). Understanding online information disclosure as a privacy calculus adjusted by exchange fairness. In ICIS 2007 Proceedings - Twenty Eighth International Conference on Information Systems.\n[25] Li, H., Sarathy, R., &Xu, H. (2010). Understanding situational online information disclosure as a privacy calculus. Journal of Computer Information Systems, 51(1), 62–71. https://doi.org/10.1080/08874417.2010.11645450\n[26] Li, H., Sarathy, R., &Xu, H. (2011). The role of affect and cognition on online consumers’ decision to disclose personal information to unfamiliar online vendors. Decision Support Systems, 51(3), 434–445. https://doi.org/10.1016/j.dss.2011.01.017\n[27] Li, Y. (2012). Theories in online information privacy research: A critical review and an integrated framework. Decision Support Systems, 54(1), 471–481. https://doi.org/10.1016/j.dss.2012.06.010\n[28] Liberman, N., Idson, L. C., Camacho, C. J., &Higgins, E. T. (1999). Promotion and prevention choices between stability and change. Journal of Personality and Social Psychology, 77(6), 1135–1145. https://doi.org/10.1037/0022-3514.77.6.1135\n[29] Liu, X. (2013). How Are People Enticed to Disclose Personal Information Despite Privacy Concerns in Social Network Sites? The Calculus Between Benefit and Cost. Journal of the American Society for Information Science and Technology, 64(July), 1852–1863. https://doi.org/10.1002/asi\n[30] Lockwood, P., Jordan, C. H., &Kunda, Z. (2002). Motivation by positive or negative role models: Regulatory focus determines who will best inspire us. Journal of Personality and Social Psychology, 83(4), 854–864. https://doi.org/10.1037/0022-3514.83.4.854\n[31] Malhotra, N. K., Kim, S. S., &Agarwal, J. (2004). Internet users’ information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information Systems Research, 15(4), 336–355. https://doi.org/10.1287/isre.1040.0032\n[32] Milne, G. R. (1997). Consumer participation in mailing lists: A field experiment. Journal of Public Policy and Marketing, 16(2), 298–309. https://doi.org/10.1177/074391569701600210\n[33] Milne, G. R., &Gordon, M. E. (1993). Direct Mail Privacy-Efficiency Trade-offs within an Implied Social Contract Framework. Journal of Public Policy & Marketing, 12(2), 206–215. https://doi.org/10.1177/074391569101200206\n[34] Milne, G. R., Pettinico, G., Hajjat, F. M., &Markos, E. (2017). Information Sensitivity Typology: Mapping the Degree and Type of Risk Consumers Perceive in Personal Data Sharing. Journal of Consumer Affairs, 51(1), 133–161. https://doi.org/10.1111/joca.12111\n[35] Mingwei Hsu, Kharlamov, A., &Glenn Parry. (2019). Managing personalization-privacy paradox of digital services: A systematic literature review. Data for Policy.\n[36] Norberg, P. A., Horne, D. R., &Horne, D. A. (2007). The privacy paradox: Personal information disclosure intentions versus behaviors. Journal of Consumer Affairs, 41(1), 100–126. https://doi.org/10.1111/j.1745-6606.2006.00070.x\n[37] Nowak, G. J., &Phelps, J. (1992). Understanding privacy concerns.An assessment of consumers’ information-related knowledge and beliefs. Journal of Direct Marketing, 6(4), 28–39. https://doi.org/10.1002/dir.4000060407\n[38] Odel, L. I. M., Ersuasion, I. N. P., &Angst, B. C. M. (2009). Adoption of electronic health records in the presence of privacy concerns: the elaboration likelihood model and individual persuasion.pdf. Management Information Systems Quarterly, 33(2), 339–370.\n[39] Pavlou, P. A., &Stewart, D. W. (2000). Measuring the Effects and Effectiveness of Interactive Advertising. Journal of Interactive Advertising, 1(1), 61–77. https://doi.org/10.1080/15252019.2000.10722044\n[40] Pham, M. T., &Avnet, T. (2004). Ideals and Oughts and the Reliance on Affect versus Substance in Persuasion. Journal of Consumer Research, 30(4), 503–518. https://doi.org/10.1086/380285\n[41] Phelps, J., Nowak, G., &Ferrell, E. (2000). Privacy concerns and consumer willingness to provide personal information. Journal of Public Policy and Marketing, 19(1), 27–41. https://doi.org/10.1509/jppm.19.1.27.16941\n[42] Pötzsch, S. (2009). Privacy awareness: A means to solve the privacy paradox? IFIP Advances in Information and Communication Technology, 298(216483), 226–236. https://doi.org/10.1007/978-3-642-03315-5_17\n[43] Rohm, A. J., &Milne, G. R. (2004). Just what the doctor ordered. The role of information sensitivity and trust in reducing medical information privacy concern. Journal of Business Research, 57(9), 1000–1011. https://doi.org/10.1016/S0148-2963(02)00345-4\n[44] Sassenberg, K., Landkammer, F., &Jacoby, J. (2014). The influence of regulatory focus and group vs. individual goals on the evaluation bias in the context of group decision making. Journal of Experimental Social Psychology, 54, 153–164. https://doi.org/10.1016/j.jesp.2014.05.009\n[45] Schoenbachler, D. D., &Gordon, G. L. (2002). Trust and customer willingness to provide information in database-driven relationship marketing. Journal of Interactive Marketing, 16(3), 2–16. https://doi.org/10.1002/dir.10033\n[46] Sharma, S., &Crossler, R. E. (2014). Disclosing too much? Situational factors affecting information disclosure in social commerce environment. Electronic Commerce Research and Applications, 13(5), 305–319. https://doi.org/10.1016/j.elerap.2014.06.007\n[47] Sheehan, K. B., &Hoy, M. G. (2000). Dimensions of Privacy Concern Among Online Consumers. Journal of Public Policy & Marketing, 19(1), 62–73.\n[48] Sheng, H., Nah, F. F. H., &Siau, K. (2008). An experimental study on ubiquitous commerce adoption: Impact of personalization and privacy concerns. Journal of the Association for Information Systems, 9(6), 344–376.\n[49] Siegrist, M., Cvetkovich, G., &Roth, C. (2000). Salient value similarity, social trust, and risk/benefit perception. Risk Analysis, 20(3), 353–362. https://doi.org/10.1111/0272-4332.203034\n[50] Sitkin, S. B., &Pablo, A. L. (1992). Reconceptualizing the Determinants of Risk Behavior Author ( s ): Sim B . Sitkin and Amy L . Pablo Source : The Academy of Management Review , Vol . 17 , No . 1 ( Jan ., 1992 ), pp . 9-38 Published by : Academy of Management Stable URL : http://www.jstor. Academy of Management, 17(1), 9–38.\n[51] Sperber, D., &Wilson, D. (1986). Relevance: Communication and Cognition. In Cambridge, MA: Harvard University Press. (Vol. 142). https://doi.org/10.1111/j.1468-0017.1989.tb00246.x\n[52] Spiekermann, S., Grossklags, J., &Berendt, B. (2001). E-privacy in 2nd generation E-commerce: Privacy preferences versus actual behavior. Proceedings of the ACM Conference on Electronic Commerce, 38–47.\n[53] Stone, D. L. (1981). The effects of the valence of outcomes for providing data and the perceived relevance of the data requested on privacy-related behaviors, beliefs, and attitudes.\n[54] Sutanto, J., Palme, E., Tan, C.-H., &Phang, C. W. (2013). Addressing the personalization-privacy paradox: an empirical assessment from a field experiment on smartphone users. MIS Quarter, 37(4), 1141–1164.\n[55] Wang, T., Duong, T. D., &Chen, C. C. (2016). Intention to disclose personal information via mobile applications: A privacy calculus perspective. International Journal of Information Management, 36(4), 531–542. https://doi.org/10.1016/j.ijinfomgt.2016.03.003\n[56] Xu, H., Luo, X., Carroll, J. M., &Rosson, M. B. (2011). The personalization privacy paradox: An exploratory study of decision making process for location-aware marketing. Decision Support Systems, 51(1), 42–52. https://doi.org/10.1016/j.dss.2010.11.017\n[57] Xu, H., Teo, H. H., Tan, B. C. Y., &Agarwal, R. (2009). The role of push-pull technology in privacy calculus: The case of location-based services. Journal of Management Information Systems, 26(3), 135–174. https://doi.org/10.2753/MIS0742-1222260305\n[58] Zhang, B., &Xu, H. (2016). Privacy nudges for mobile applications: Effects on the creepiness emotion and privacy attitudes. Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, 27, 1676–1690. https://doi.org/10.1145/2818048.2820073\n[59] Zhang, E. M. (2010). Beauty as a tool: The effect of model attractiveness, product relevance, and elaboration likelihood on advertising effectiveness. Psychology & Marketing, 30(6), 461–469. https://doi.org/10.1002/mar\n[60] Zhou, T. (2011). The impact of privacy concern on user adoption of location-based services. In Industrial Management and Data Systems (Vol. 111, Issue 2, pp. 212–226). https://doi.org/10.1108/02635571111115146\n[61] Zhu, Y. Q., &Chang, J. H. (2016). The key role of relevance in personalized advertisement: Examining its impact on perceptions of privacy invasion, self-awareness, and continuous use intentions. Computers in Human Behavior, 65, 442–447. https://doi.org/10.1016/j.chb.2016.08.048\n[62] Zimmer, J. C., Arsal, R. E., Al-Marzouq, M., &Grover, V. (2010). Investigating online information disclosure: Effects of information relevance, trust and risk. Information and Management, 47(2), 115–123. https://doi.org/10.1016/j.im.2009.12.003; G0107356029; https://nccur.lib.nccu.edu.tw//handle/140.119/131499; https://nccur.lib.nccu.edu.tw/bitstream/140.119/131499/1/602901.pdf
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Témata: 計劃行為理論, 知識分享, 虛擬社群, 沈浸, 共同依附, 線上遊戲, Theory of planned behavior, knowledge sharing, Virtual Community, immersion, Codependency, Online Game
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Relation: 1. Ajzen I. (1991). The theory of planned behavior. Organizational Behavior & Human Decision Process, 50, 179-211. 2. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior Springer. 3. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. 4. Algesheimer, R., Dholakia, U. M., & Herrmann, A. (2005). The social influence of brand community: Evidence from european car clubs. Journal of Marketing, 69(3), 19-34. 5. Armstrong, A. G. and J. Hagel. (1996). The real value of on-line communities. Harvard Business Review, 74(3), 134-140. 6. Autenshlyus, Y. b. (2008). Codependence and post-traumatic stress disorders. International Journal of Psychophysiology, 69, 276-316. 7. Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The role of emotions in marketing. Journal of the Academy of Marketing Science, 27(2), 184-206. 8. Cermak, T. L. (1991). Co-addiction as a disease. Psychiatric Annals, 21(5), 266-272. 9. Chan, C. M. L., Bhandar, M., Oh, L., & Chan, H. (2004). Recognition and participation in a virtual community. Paper presented at the System Sciences, 2004. Proceedings of the 37th Annual Hawaii International Conference On, 10 pp. 10. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336. 11. Choi D , J Kim. (2004). Why people continue to play online games: In search of critical design factors to increase customer loyalty to online contents. CYBERPSYCHOLOGY & BEHAVIOR, 7(1), 11-24. 12. Crawford, C. (2003). In Williams R. (Ed.), Chris crawford on game design [動畫基礎技法. (龍溪出版社)] Indianapolis: New Riders. 13. Csikszentmihalyi, M. (1975). Play and intrinsic rewards. Journal of Humanistic Psychology, 14. Csikszentmihalyi, M., & LeFevre, J. (1989). Optimal experience in work and leisure. Journal of Personality and Social Psychology, 56(5), 815. 15. Curtis P. (1992). Mudding: Social phenomena in text-based virtual realities. Directions and Implications of Advanced Computing, 16. Darr, E. D., & Kurtzberg, T. R. (2000). An investigation of partner similarity dimensions on knowledge transfer. Organizational Behavior and Human Decision Processes, 82(1), 28-44. 17. Davenport, T. H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know Harvard Business Press. 18. Dubinsky, A. J., & Loken, B. (1989). Analyzing ethical decision making in marketing. Journal of Business Research, 19(2), 83-107. 19. Fishbein M, A. I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research, reading Addison-Wesley. 20. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, , 39-50. 21. Gupta, A. K., & Govindarajan, V. (2000). Knowledge flows within multinational corporations. Strategic Management Journal, 21(4), 473-496. 22. Ha, I., Yoon, Y., & Choi, M. (2007). Determinants of adoption of mobile games under mobile broadband wireless access environment. Information & Management, 44(3), 276-286. 23. Hagel III, J., & Armstrong, A. G. (1997). Netgain, harvard business school press. Boston, MA, 24. Hagel, J., & Armstrong, A. (1997). Net gain: Expanding markets through virtual communities Harvard Business Press. 25. Hair Jr, J. F.,Hult, G. T. M.,Ringle,C., & Sarstedt, M. (2013). A primer on parital least squares structural equation modeling(PLS-SEM)SAGE publications. Incorporated, 26. Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM) Sage Publications. 27. Hands, M., & Dear, G. (1994). Co‐dependency: A critical review. Drug and Alcohol Review, 13(4), 437-445. 28. Hatterer, L. (1994). Addictive process, encyclopedia of psychology. NY: John Wiley & Sons, 29. Hendriks, P. (1999). Why share knowledge?the influence of ICT on motivation for knowledge sharing. Knowledge and Process Management, 6(2), 91-100. 30. Hoffman L. D. , Novak P. T. (1996). Marketing in hypermedia computer-mediated environments conceptual foundations. Journal of Marketing, 60(7), 50-68. 31. Hughes-Hammer, C,Martstolf,D.S. & Zeller, R.A. (1998). Development and testing of the codependency assessment tool. Archives of Psychiatric Nursing, 12(5), 264-272. 32. Johnson, D. and J. Wiles. (2003). Effective affective user interface design in games. Ergonomics, 46(13-14), 1332-1345. doi:doi:10.1080/00140130310001610865 33. Kassem, N. O., Lee, J. W., Modeste, N. N., & Johnston, P. K. (2003). Understanding soft drink consumption among female adolescents using the theory of planned behavior. Health Education Research, 18(3), 278-291. 34. Kim, K. H., Park, J. Y., Kim, D. Y., Moon, H. I., & Chun, H. C. (2002). E-lifestyle and motives to use online games. Irish Marketing Review, 15(2), 71. 35. Koh, J., Kim, Y., & Kim, Y. (2003). Sense of virtual community: A conceptual framework and empirical validation. International Journal of Electronic Commerce, 8(2), 75-94. 36. Lee, M. (2009). Understanding the behavioural intention to play online games: An extension of the theory of planned behaviour. Online Information Review, 33(5), 849-872. 37. McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: A trust building model. The Journal of Strategic Information Systems, 11(3), 297-323. 38. Nick, Y. (2006). Running head: MMORPG DEMOGRAPHICS, MOTIVATIONS, AND EXPERIENCES. Teleoperators and Virtual Environments, (15), 309-329. 39. Nonaka, I., & Takeuchi, H. (1997). The knowledge-creating company. The Economic Impact of Knowledge, , 183. 40. Nonaka, I., & Takeuchi, H. (1995). The knowledge creation company: How japanese companies create the dynamics of innovation. Oxford University Press.New York, USA, , 304. 41. Novak, T. P., Hoffman, D. L., & Duhachek, A. (2003). The influence of goal-directed and experiential activities on online flow experiences. Journal of Consumer Psychology, 13(1), 3-16. 42. Nunnally, J. C., & Bernstein, I. (1994). The assessment of reliability. Psychometric Theory, 3(1), 248-292. 43. P. Sweetser and P. Wyeth. (2005). GameFlow: A model for evaluating player enjoyment in games. ACM Computers in Entertainment, 3(3), 1-23. 44. Purser, R. E., & Pasmore, W. A. (1992). Organizing for learning. Research in Organizational Change and Development, 6(3), 7-114. 45. Rollings, A., & Adams, E. (2003). Andrew rollings and ernest adams on game design New Riders. 46. Rouse, R. (2001). In Plano (Ed.), Game design: Theory and practice Word ware. 47. Ruggles, R. (2009). Knowledge management tools Routledge. 48. Sherry, J. L. (2004). Flow and media enjoyment. Communication Theory, 14(4), 328-347. 49. Song, S., & Lee, J. (2007). RETRACTED: Key factors of heuristic evaluation for game design: Towards massively multi-player online role-playing game. International Journal of Human-Computer Studies, 65(8), 709-723. 50. Taylor, S., & Todd, P. (1995). Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12(2), 137-155. 51. Thomas-Hunt, M. C., Ogden, T. Y., & Neale, M. A. (2003). Who''s really sharing? effects of social and expert status on knowledge exchange within groups. Management Science, 49(4), 464-477. 52. Urbach, N., & Ahlemann, F. (2010). Structural equation modeling in information systems research using partial least squares. JITTA: Journal of Information Technology Theory and Application, 11(2), 5. 53. Wang, Y., Wang, Y., Lin, H., & Tang, T. (2003). Determinants of user acceptance of internet banking: An empirical study. International Journal of Service Industry Management, 14(5), 501-519. 54. Wasko, M. M., & Faraj, S. (2000). “It is what one does”: Why people participate and help others in electronic communities of practice. The Journal of Strategic Information Systems, 9(2), 155-173. 55. Wasko, M. M., & Faraj, S. (2005). Why should I share? examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, , 35-57. 56. Wellman, B. (1982). Studying personal communities. Social Structure and Network Analysis, , 61-80. 57. Yao, M. Z., & Flanagin, A. J. (2006). A self-awareness approach to computer-mediated communication. Computers in Human Behavior, 22(3), 518-544. doi:http://dx.doi.org.ezproxy.lib.tku.edu.tw/10.1016/j.chb.2004.10.008 58. 余泰魁 、鄭時宜 , (2005). 影響虛擬社群線上行為因素之研究. 國立金門技術學院學報, (1), 91-102. 59. 余泰魁 、鄭時宜. (2004). 虛擬社群線上聊天行為模式之研究. Electronic Commerce Studies, 2(2), 117-135. 60. 侯正裕. (2011). 「遷移到虛擬新世界」—以人口遷移理論探討MMORPG. 中山管理評論, 19(1), 141-172. 61. 劉上裕 、葉榮椿 、王子玲 、黃宏隆等 . (2011). 影響線上遊戲玩家使用行為相關因素之研究. 美和學報, 30(1), 147-172. 62. 劉月純. (2012). 臺灣遊戲產業發展與全球趨勢分析. 臺北: 財團法人資訊工業策進會產業情報研究所（MIC）. 63. 張世宗. (2006). 游藝學-傳統童玩與現代兒童. 歷史月刊, (224), 4-10. 64. 張意珮. (2002). 線上遊戲使用者轉換因素之研究 ,Available from AiritiLibrary. 65. 彭淑芸、饒培倫、楊錦洲等. (2004). 網路沉迷要素關連性模型之建構與分析. 師大學報: 人文與社會科學類, 49(2), 67-84. 66. 徐嘉靖,、許尚華. (2009). 探索多人線上角色扮演遊戲的遊戲社群社交互動性因素,碩士論文, 國立交通大學工業工程與管理系所 67. 朱文禎、陳哲賢. (2007 年春季). 探討虛擬社群之知識分享行為:以線上遊戲社群為例. 電子商務研究, 第五卷(第一期), 55-80. 68. 林倩如、王智弘,、林旻沛等. (2012). 網路成癮傾向兒童之短期動力取向團體心理治療方案. 中華團體心理治療, 18(4), 11-27. 69. 林東清. (2007), 知識管理 (再版), 台北市: 智勝文化. 70. 童國偉. (2011). 以同儕互動理論分析知識分享之影響因素. 嶺東科技大學資訊管理與應用研究所學位論文, , 1-39. 71. 羅家德. (1999). 虛擬社群版主特質對經營績效之影響-以CityFamily網路同學會為例, 學位論文, 國立中山大學 72. 翁漢騰 、張世宗 、張恬君等 . (2010). 單人動作遊戲之創作元素分析. [creative element analysis of single player action game]. 商業設計學報, (14), 83-96. 73. 莊丙農. (2008). 從沈浸理論探討免費線上遊戲玩家對購買電腦周邊產品行為意圖之研究 (碩士論文). 74. 莊智凱 、周長青 、李建邦等 . (2014). 探討Facebook涉入程度、人格特質與網際人關係對路成癮之影響. Journal of Data Analysis, 9(3), 165-186. 75. 葉建亨 、黃文楨. (2011). 整合社會資本與社會交換理論探討虛擬社群知識分享意願. 資訊管理學報, 18(3), 75-99. 76. 葉思義 、宋昀璐 . (2004). 數位遊戲設計：遊戲設計知識全領域. 台北: 碁峰資訊. 77. 謝佩玲. (2014). 影響線上遊戲玩家沈浸與價值共創因素之研究. [DOI:10.6510/JTLM.2(2).15] 觀光與休閒管理期刊, 2(2), 197-211. 78. 邱光輝 、紀東昀 . (2014). 共依附對虛擬社群成員繼續分享知識意圖之影響. 輔仁管理評論, 21(1), 1-32. 79. 郭冠樟 、葉乘豪 . (2012 年夏季). 以沉浸理論、網路外部性、計畫行為理論探討體感遊戲機購買意圖之研究. 電子商務研究, 10(2), 199-216. 80. 陳俐文. (2010). 結合棒球轉播及線上文字報導建構以事件為主之影片擷取系統 (碩士論文). Available from 國立雲林科技大學資訊工程研究所碩士班. 81. 陳怡安. (2003). 線上遊戲的魅力-以重度玩家為例 (碩士論文).南華大學 82. 陳秀菁 、吳麗娟 、林世華等. (2004). 大學生的共依附特質、人際親密能力與親密感之相關研究. 教育心理學報, 36(2), 145-164. 83. 陳美如 、王渝薇 、范錚強等 . (2016). 玩線上遊戲是計劃行為嗎? 從非計劃型的因素探討. 資訊管理學報, 23(2), 217-245. 84. 黃彥達. (2015). 數位時代論壇. New York: 85. 黃日鉦 、林承賢. (2013). 以計畫行為理論探討縮短數位落差之持續使用行為. International Journal, 5(1), 057-078.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/114500; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/114500/1/index.html
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Témata: 計劃行為理論, 知識分享, 虛擬社群, 沈浸, 共同依附, 線上遊戲, Theory of planned behavior, knowledge sharing, Virtual Community, immersion, Codependency, Online Game, info, socio
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Témata: 意見探勘, 意見單元, 影響力分析, Opinion Mining, Opinion unit, Influence analysis
Relation: 中文部分 [1] 石矛、方勇、曾祥平、王長輝，《IDM 模型分析及其影响力改进算法》， 成都信息工程学院学报，23(1)，69-72，2008。 [2] 朱嫣岚、闵锦、周雅倩、黄萱菁、吴立德，《基于 Hownet 的词汇语义倾向计算》，中文信息学报，20(1)，14-20，2012。 [3] 何韜、胡勇、吳越，《基于影响力形成的论坛意见领袖识别》，信息安全与通信保密，(6)，81-83，2012。 [4] 肖宇、許煒、夏霖，《一种基于情感倾向分析的网络团体意见领袖识别算法》， 计算机科学， 39(2)，34-37，2012。 [5] 李孟潔、張俊盛，《利用機器學習作法之中文意見分析》，碩士論文，國立清華大學資訊科學與工程研究所，2009。 [6] 孫瑛澤、陳建良、劉峻杰、劉昭麟、蘇豐文，〈中文短句之情緒分類〉，2010自然語言與語音處理研討會，頁184-198，暨南大學，2010。 [7] 陳柏翰、蕭瑞祥，《基於中文語法規則的意見單元抽取方法之研究》，碩士論文，淡江大學資訊管理研究所，2013。 [8] 陳維君、蕭瑞祥，《網路意見分析與傳統意見調之比較》，碩士論文，淡江大學資訊管理研究所，2013。 [9] 崔懷芝，〈量表信度的測量： kappa 統計量之簡介〉，網址：http://biostatistics.cmu.edu.tw/online/teaching_corner_011.pdf， 上網日期：2014年2月。 [10] 邱鴻達、梁婷，《意見探勘在中文電影評論之應用》，碩士論文，國立交通大學資訊工程研究所，2011。 [11] 黃婷穎、莊裕澤，《網路評價視覺化》，碩士論文，國立台灣大學資訊管理研究所，2011。 [12] 簡之文、蕭瑞祥，《部落格文章情感分析之研究》，碩士論文，淡江大學資訊管理研究所，2012。 [13] 楊盛帆、陸承志，《以整合式規則來做網路論壇上的3C 產品口碑分析》，碩士論文，元智大學資訊管理研究所，2009。 [14] 劉瀚之、王正豪，《微網誌訊息影響力分析及回應意見評價之研究》，碩士論文，國立台北科技大學資訊工程研究所，2012。 [15] 樊興華、趙靜、方濱興、李欲曉，《影响力扩散概率模型及其用于意见领袖发现研究》，计算机学报，36(2)，360-367，2013。 [16] 樊興華、吳昊，《意见领袖识别中的文本倾向性研究》，计算机应用研究，30(9)，2613-2615，2013。 英文部分 [17] Bodendorf, F., and Kaiser, C., "Detecting opinion leaders and trends in online social networks," Proceedings of the 2nd ACM workshop on Social web search and mining, pp. 65-68, 2009. [18] Ding, X., Liu, B., and Yu, P. S., "A holistic lexicon-based approach to opinion mining," Proceedings of the International Conference on Web Search and Web Data Mining, pp. 231-240. 2008. [19] Forman, C., Ghose, A., and Wiesenfeld, B., "Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets," Information Systems Research, vol. 19, no 3, pp. 291-313, 2008. [20] Hu, M., and Liu, B., "Mining Opinion Features in Customer Reviews," Proceedings of the 19th National Conference on Artificial Intelligence, SanJose, California, United States, pp. 755-760, 2004. [21] Hu, M., and Liu, B., "Mining and Summarizing Customer Reviews," Proceedings of the 10th ACM International Conference on Knowledge Discovery and Data Mining, Seattle, Washington, United States, pp. 168-174, 2004. [22] Hu, N., Liu, L., and Zhang, J., "Do online reviews affect product sales? The role of reviewer characteristics and temporal effects," Information Technology and Management, vol. 9, no 3, pp. 201-214, 2008. [23] Kim, S. M., and Hovy, E., "Determining the sentiment of opinions," Proceedings of the COLING conference, pp. 1367-1374, 2004. [24] Liu, B., Hu, M., and Cheng, J., "Opinion Observer: Analyzing and Comparing Opinions on the Web, " Proceedings of the 14th international Conference on World Wide Web, Chiba, Japan, pp. 342-351, 2005. [25] Liu, B., "Sentiment Analysis and Subjectivity." in Handbook of Natural Language Processing, 2nd Ed. CRC Press, pp. 627-666, 2010. [26] Latané, B., "Psychology of social impact," American Psychologist, 36,pp. 343-356. 1981. [27] Nunamaker, J. R., Chen, J. F., and Purdin, T. D. M., "Systems Development in Information Systems Research," Journal of Management Information Systems, vol. 7, no. 3, pp. 89-106, 1990-1991. [28] Matsumura, N., Ohsawa, Y., and Ishizuka, M., "Influence diffusion model in text-based communication," Transactions of the Japanese Society for Artificial Intelligence, vol. 17, no. 3, pp. 259-267, 2002. [29] Turney, P. D., "Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews," Proceedings of the 40th annual meeting on association for computational linguistics, pp. 417-424, 2002. [30] Wang, J. H., Fu, T., Lin, H. M., and Chen, H., "A framework for exploring gray web forums: analysis of forum-based communities in Taiwan," In Intelligence and Security Informatics, Springer Berlin Heidelberg pp. 498-503, 2006. [31] Wang, J. H., and Lee, C. C., "Unsupervised Opinion Phrase Extraction and Rating in Chinese Blog Posts," Proceedings of the 3rd IEEE International Conference on Social Computing (SocialCom), Boston, USA, pp.820-823, 2011. [32] Yang, C. C., Tang, X., and Thuraisingham, B. M., "An analysis of user influence ranking algorithms on Dark Web forums," In ACM SIGKDD Workshop on Intelligence and Security Informatics, pp. 10, 2010.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/102368
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Témata: 意見探勘, 意見單元, 影響力分析, Opinion Mining, Opinion unit, Influence analysis, manag, envir
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Témata: 情感運算, 服務科學, 服務補救, 類神經網路, 決策樹, Affective computing, Service science, service recovery, artificial neural networks, Decision tree
Relation: 參考文獻 [1] 行政院，，網址：http://www.dgbas.gov.tw/public/data/dgbas03/bs4/nis93/ni.pdf [2] Abdel-Hamid, O., Mohamed, A. R., Jiang, H., & Penn, G. (2012). Applying convolutional neural networks concepts to hybrid NN-HMM model for speech recognition. In Acoustics, Speech and Signal Processing (ICASSP), 2012, March IEEE International Conference on (pp. 4277-4280). IEEE. [3] Abe, T. (2005). What is service science. FRI Research Report no. 246, Fujitsu Research Institute, [4] Alter, S. (2011). Making a science of service systems practical: Seeking usefulness and understandability while avoiding unnecessary assumptions and restrictions. In The Science of Service Systems (pp. 61-72). Springer US. [5] Alter, S. (2012). Challenges for service science. Journal of Information Technology Theory and Application, 13(2), 22-38. [6] Bachu, R., Kopparthi, S., Adapa, B., & Barkana, B. (2008). Separation of voiced and unvoiced using zero crossing rate and energy of the speech signal. American Society for Engineering Education (ASEE), Zone Conference Proceedings, 1-7. [7] Baranyi, P., & Csapo, A. (2012). Definition and synergies of cognitive infocommunications. Acta Polytechnica Hungarica, 9(1), 67-83. [8] Barile, S., & Polese, F. (2010). Smart service systems and viable service systems: Applying systems theory to service science. Service Science, 2(1-2), 21-40. [9] Bengio, Y., & Grandvalet, Y. (2003). No unbiased estimator of the variance of K-fold cross-validation. CIRANO. [10] Bitner, M. J., Booms, B. H., & Mohr, L. A. (1994). Critical service encounters: The employee''s viewpoint. The Journal of Marketing, 58(4), 95-106. [11] Bitner, M. J., Booms, B. H., & Tetreault, M. S. (1990). The service encounter: Diagnosing favorable and unfavorable incidents. Journal of Marketing, 54(1), 71-84. [12] Bratko, I., & Muggleton, S. (1995). Applications of inductive logic programming. Communications of the ACM, 38(11), 65-70. [13] Brooke, J. (1996). SUS-A quick and dirty usability scale. Usability Evaluation in Industry, 189, 194. [14] Burkhardt, F., Paeschke, A., Rolfes, M., Sendlmeier, W. F., & Weiss, B. (2005). A database of german emotional speech. Interspeech, Vol. 5, 1517-1520 [15] Busso, C., Deng, Z., Yildirim, S., Bulut, M., Lee, C. M., Kazemzadeh, A Narayanan, S. (2004). Analysis of emotion recognition using facial expressions, speech and multimodal information. Proceedings of the 6th International Conference on Multimodal Interfaces, 205-211. [16] Cambria, E., Livingstone, A., & Hussain, A. (2012). The hourglass of emotions. In Cognitive behavioural systems, Vol. 74(3), 144-157. Springer Berlin Heidelberg. [17] Chang, P., Wang, Y., & Tsai, C. (2005). Evolving neural network for printed circuit board sales forecasting. Expert Systems with Applications, 29(1), 83-92. [18] Chebat, J., & Slusarczyk, W. (2005). How emotions mediate the effects of perceived justice on loyalty in service recovery situations: An empirical study. Journal of Business Research, 58(5), 664-673. [19] Chung, B. G., & Hoffman, K. D. (1998). Critical incidents: Service failures that matter most. The Cornell Hotel and Restaurant Administration Quarterly, 39(3), 66-71. [20] Coiera, E. (2003). Interaction design theory. International Journal of Medical Informatics, 69(2), 205-222. [21] Coleman, T., Branch, M. A., & Grace, A. (1999). Optimization toolbox. For use with MATLAB.User’s Guide for MATLAB 5, Version 2, Relaese II, [22] Conlon, D. E., & Murray, N. M. (1996). Customer perceptions of corporate responses to product complaints: The role of explanations. Academy of Management Journal, 39(4), 1040-1056. [23] Demirkan, H., Kauffman, R. J., Vayghan, J. A., Fill, H., Karagiannis, D., & Maglio, P. P. (2009). Service-oriented technology and management: Perspectives on research and practice for the coming decade. Electronic Commerce Research and Applications, 7(4), 356-376. [24] DeWitt, T., Nguyen, D. T., & Marshall, R. (2008). Exploring customer loyalty following service recovery the mediating effects of trust and emotions. Journal of Service Research, 10(3), 269-281. [25] Douglas-Cowie, E., Campbell, N., Cowie, R., & Roach, P. (2003). Emotional speech: Towards a new generation of databases. Speech Communication, 40(1), 33-60. [26] Dube, L., & Menon, K. (2000). Multiple roles of consumption emotions in post-purchase satisfaction with extended service transactions. International Journal of Service Industry Management, 11(3), 287-304. [27] Fahlman, S. E. (1988). An empirical study of learning speed in back-propagation networks. [28] Ferrario, R., Guarino, N., Janiesch, C., Kiemes, T., Oberle, D., & Probst, F. (2011). Towards an ontological foundation of services science: The general service model. [29] Fragopanagos, N., & Taylor, J. G. (2005). Emotion recognition in human–computer interaction. Neural Networks, 18(4), 389-405. [30] Fredrickson, B. L. (2002). Positive emotions. Handbook of Positive Psychology, Vol. 3, 120-134. [31] Gharavian, D., Sheikhan, M., Nazerieh, A., & Garoucy, S. (2012). Speech emotion recognition using FCBF feature selection method and GA-optimized fuzzy ARTMAP neural network. Neural Computing and Applications, 21(8), 2115-2126. [32] Gronroos, C. (1988). Service quality: The six criteria of good perceived service quality. Review of Business, 9(3), 10-13 [33] Gronroos, C., & Gummerus, J. (2014). The service revolution and its marketing implications: service logic vs service-dominant logic. Managing Service Quality, 24(3), 206-229. [34] Gronroos, C., & Gummerus, J. (2014). The service revolution and its marketing implications: Service logic versus service-dominant logic. Managing Service Quality, 24(3), 1-1. [35] Guo, Z., Zhao, W., Lu, H., & Wang, J. (2012). Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model. Renewable Energy, 37(1), 241-249. [36] Hall, M. A., & Holmes, G. (2003). Benchmarking attribute selection techniques for discrete class data mining. Knowledge and Data Engineering, IEEE Transactions on, 15(6), 1437-1447. [37] Han, J., Kamber, M., & Pei, J. (2006). Data mining: Concepts and techniques Morgan kaufmann. [38] Han, W., Chan, C., Choy, C., & Pun, K. (2006). An efficient MFCC extraction method in speech recognition. Circuits and Systems, 2006. ISCAS 2006. Proceedings. 2006 IEEE International Symposium on, 4, 145-148. [39] Hariharan, M., Saraswathy, J., Sindhu, R., Khairunizam, W., & Yaacob, S. (2012). Infant cry classification to identify asphyxia using time-frequency analysis and radial basis neural networks. Expert Systems with Applications, 39(10), 9515-9523. [40] Hart, C. W., Heskett, J. L., & Sasser, W. E.,Jr. (1990). The profitable art of service recovery. Harvard Business Review, 68(4), 148-156. [41] Hayes-Roth, B., Ball, G., Lisetti, C., Picard, R. W., & Stern, A. (1998). Panel on affect and emotion in the user interface. International Conference on Intelligent User Interfaces: Proceedings of the 3 Rd International Conference on Intelligent User Interfaces, 6(09), 91-94. [42] Hecht-Nielsen, R. (1989). Theory of the backpropagation neural network. Neural Networks, 1989. IJCNN., International Joint Conference on, 593-605. [43] Hess, R. L., Ganesan, S., & Klein, N. M. (2003). Service failure and recovery: The impact of relationship factors on customer satisfaction. Journal of the Academy of Marketing Science, 31(2), 127-145. [44] Hinton, G. E., Srivastava, N., Krizhevsky, A., Sutskever, I., & Salakhutdinov, R. R. (2012). Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint arXiv:1207.0580. [45] Hoffman, K. D., Kelley, S. W., & Rotalsky, H. M. (1995). Tracking service failures and employee recovery efforts. Journal of Services Marketing, 9(2), 49-61. [46] Holmlid, S. (2009). Interaction design and service design: Expanding a comparison of design disciplines. Nordes, (2), 157-164. [47] Holmlid, S., & Evenson, S. (2008). Bringing service design to service sciences, management and engineering. Service science, management and engineering education for the 21st century (pp. 341-345) Springer. [48] Huang, H. C. (2012). Using artificial neural networks to predict restaurant industry service recovery. International Journal of Advancements in Computing Technology, 4(10), 315-321. [49] Huang, K. Y. (2009). Challenges in human-computer interaction design for mobile devices. In Proceedings of the World Congress on Engineering and Computer Science, Vol. 1, 236-241. [50] IBM Research (2004). Services science: a new academic discipline? A 120-page report of a two-day summit entitled Architecture of On-Demand Business, May 17-18, 2004. [51] Inanoglu, Z., & Caneel, R. (2005). Emotive alert: HMM-based emotion detection in voicemail messages. Proceedings of the 10th International Conference on Intelligent User Interfaces, 251-253. [52] Ingale, A. B., & Chaudhari, D. S. (2012). Speech emotion recognition. International Journal of Soft Computing and Engineering (IJSCE) ISSN, 2231-2307. [53] Izgi, E., Oztopal, A., Yerli, B., Kaymak, M. K., & Şahin, A. D. (2012). Short–mid-term solar power prediction by using artificial neural networks. Solar Energy, 86(2), 725-733. [54] Jiang, N., Zhao, Z., & Ren, L. (2003). Design of structural modular neural networks with genetic algorithm. Advances in Engineering Software, 34(1), 17-24. [55] Junginger, S., & Sangiorgi, D. (2009). Service design and organizational change: Bridging the gap between rigour and relevance. 3rd IASDR Conference on Design Research, Seoul, Korea, [56] Jyh-Shing Roger Jang, "Audio Signal Processing and Recognition," (in Chinese) available at the links for on-line courses at the author''s homepage athttp://www.cs.nthu.edu.tw/~jang. [57] Kaliouby, R. e., Picard, R., & BARON‐COHEN, S. (2006). Affective computing and autism. Annals of the New York Academy of Sciences, 1093(1), 228-248. [58] Kelley, S. W., Hoffman, K. D., & Davis, M. A. (1994). A typology of retail failures and recoveries. Journal of retailing, 69(4), 429-452. [59] Kinnunen, T. (2002). Designing a speaker-discriminative adaptive filter bank for speaker recognition. In INTERSPEECH. [60] Kohavi, R. (1995). A study of cross-validation and bootstrap for accuracy estimation and model selection. Ijcai, 14(2), 1137-1145. [61] Kollias, S., & Karpouzis, K. (2005). Multimodal emotion recognition and expressivity analysis. Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on, 779-783. [62] Komunda, M., & Osarenkhoe, A. (2012). Remedy or cure for service failure? Effects of service recovery on customer satisfaction and loyalty. Business Process Management Journal, 18(1), 82-103. [63] Koolagudi, S. G., & Rao, K. S. (2012). Emotion recognition from speech using source, system, and prosodic features. International Journal of Speech Technology, 15(2), 265-289. [64] Kort, B., Reilly, R., & Picard, R. W. (2001). An affective model of interplay between emotions and learning: Reengineering educational pedagogy-building a learning companion. Advanced Learning Technologies, 2001. Proceedings. IEEE International Conference on, 43-46. [65] Krothapalli, S. R., Yadav, J., Sarkar, S., Koolagudi, S. G., & Vuppala, A. K. (2012). Neural network based feature transformation for emotion independent speaker identification. International Journal of Speech Technology, 15(3), 335-349. [66] Lee, C. M., & Narayanan, S. S. (2005). Toward detecting emotions in spoken dialogs. Speech and Audio Processing, IEEE Transactions on, 13(2), 293-303. [67] Lee, T. (2004). Back-propagation neural network for long-term tidal predictions. Ocean Engineering, 31(2), 225-238. [68] Lek, S., & Guegan, J. (1999). Artificial neural networks as a tool in ecological modelling, an introduction. Ecological Modelling, 120(2), 65-73. [69] Leon, E., Clarke, G., Callaghan, V., & Sepulveda, F. (2004). Real-time detection of emotional changes for inhabited environments. Computers & Graphics, 28(5), 635-642. [70] Leon, E., Clarke, G., Callaghan, V., & Sepulveda, F. (2007). A user-independent real-time emotion recognition system for software agents in domestic environments. Engineering Applications of Artificial Intelligence, 20(3), 337-345. [71] Lewis, B. R., & Spyrakopoulos, S. (2001). Service failures and recovery in retail banking: The customers’ perspective. International Journal of Bank Marketing, 19(1), 37-48. [72] Li, Q., Zheng, J., Tsai, A., & Zhou, Q. (2002). Robust endpoint detection and energy normalization for real-time speech and speaker recognition. Speech and Audio Processing, IEEE Transactions on, 10(3), 146-157. [73] Li, W., Zhang, Y., & Fu, Y. (2007). Speech emotion recognition in e-learning system based on affective computing. Natural Computation, 2007. ICNC 2007. Third International Conference on, Vol. 5, 809-813. [74] Liao, W., Yang, D., & Hung, M. (2010). An intelligent recommendation model with a case study on u-tour taiwan of historical momuments and cultural heritage. Technologies and Applications of Artificial Intelligence (TAAI), 2010 International Conference on, 72-79. [75] Lisetti, C., Nasoz, F., LeRouge, C., Ozyer, O., & Alvarez, K. (2003). Developing multimodal intelligent affective interfaces for tele-home health care. International Journal of Human-Computer Studies, 59(1), 245-255. [76] Litman, D., & Forbes, K. (2003). Recognizing emotions from student speech in tutoring dialogues. Automatic Speech Recognition and Understanding, 2003. ASRU''03 2003. IEEE Workshop on, 25-30. [77] Logan, B. (2000). Mel frequency cepstral coefficients for music modeling. ISMIR. [78] Lusch, R. F. (2011). Reframing supply chain management: a service‐dominant logic perspective. Journal of Supply Chain Management, 47(1), 14-18. [79] Lusch, R. F., & Vargo, S. L. (2006). Service-dominant logic: Reactions, reflections and refinements. Marketing Theory, 6(3), 281-288. [80] Lusch, R. F., & Vargo, S. L. (2011). Service-dominant logic: A necessary step. European Journal of Marketing, 45(7/8), 1298-1309. [81] Lusch, R. F., Vargo, S. L., & Tanniru, M. (2010). Service, value networks and learning. Journal of the Academy of Marketing Science, 38(1), 19-31. [82] Madikeri, S. R., & Murthy, H. A. (2011). Mel filter bank energy-based slope feature and its application to speaker recognition. Communications (NCC), 2011 National Conference on, 1-4. [83] Maglio, P. P., Srinivasan, S., Kreulen, J. T., & Spohrer, J. (2006). Service systems, service scientists, SSME, and innovation. Communications of the ACM, 49(7), 81-85. [84] Mao, X., Zhang, B., & Luo, Y. (2007). Speech emotion recognition based on a hybrid of HMM/ANN. Proceedings of the 7th Conference on 7th WSEAS International Conference on Applied Informatics and Communications, 367-370. [85] Mattila, A. S. (1999). An examination of factors affecting service recovery in a restaurant setting. Journal of Hospitality & Tourism Research, 23(3), 284-298. [86] Miller, J. L., Craighead, C. W., & Karwan, K. R. (2000). Service recovery: A framework and empirical investigation. Journal of Operations Management, 18(4), 387-400. [87] Murty, K. S. R., & Yegnanarayana, B. (2006). Combining evidence from residual phase and MFCC features for speaker recognition. Signal Processing Letters, IEEE, 13(1), 52-55. [88] Ng, I., Maull, R., & Smith, L. (2011). Embedding the new discipline of service science. The science of service systems (pp. 13-35) Springer. [89] Ng, I., Parry, G., Smith, L., Maull, R., & Briscoe, G. (2012). Transitioning from a goods-dominant to a service-dominant logic: Visualising the value proposition of Rolls-Royce. Journal of Service Management, 23(3), 416-439. [90] Nicholson, J., Takahashi, K., & Nakatsu, R. (2000). Emotion recognition in speech using neural networks. Neural Computing & Applications, 9(4), 290-296. [91] Nilsson, M., & Ejnarsson, M. (2002). Speech recognition using hidden markov model. Department of Telecommunications and Speech Processing, Blekinge Institute of Technology. [92] Nwe, T. L., Foo, S. W., & De Silva, L. C. (2003). Speech emotion recognition using hidden markov models. Speech Communication, 41(4), 603-623. [93] Pahlavan, R., Omid, M., & Akram, A. (2012). Energy input–output analysis and application of artificial neural networks for predicting greenhouse basil production. Energy, 37(1), 171-176. [94] Petrushin, V. (1999). Emotion in speech: Recognition and application to call centers. Proceedings of Artificial Neural Networks in Engineering, pp. 7-10. [95] Picard, R. W. (1999). Affective computing for HCI. Proceedings of HCI International (the 8th International Conference on Human-Computer Interaction) on Human-Computer Interaction: Ergonomics and User Interfaces, Vol. 1. 829-833. [96] Picard, R. W. (2002). Affective medicine: Technology with emotional intelligence. Studies in Health Technology and Informatics, 80, 69-84. [97] Picard, R. W. (2003). Affective computing: Challenges. International Journal of Human-Computer Studies, 59(1), 55-64. [98] Picard, R. W. (1997) Affective computing. The MIT Press. [99] Portnoff, M. (1976). Implementation of the digital phase vocoder using the fast fourier transform.Acoustics, Speech and Signal Processing, IEEE Transactions on, 24(3), 243-248. [100] Quinlan, J. R. (1996). Improved use of continuous attributes in C4.5. [101] Quinlan, J. R. (1986). Induction of decision trees. Machine learning, 1(1), 81-106. [102] Quinlan, J. R. (1993). C4. 5: programs for machine learning, Vol. 1. [103] Rabiner, L. R., & Schafer, R. W. (1979). Digital processing of speech signals IET. [104] Ratanamahatana, C. a., & Gunopulos, D. (2003). Feature selection for the naive bayesian classifier using decision trees. Applied Artificial Intelligence, 17(5-6), 475-487. [105] Reed, R. (1993). Pruning algorithms-a survey. Neural Networks, IEEE Transactions on, 4(5), 740-747. [106] Ren, F., & Quan, C. (2012). Linguistic-based emotion analysis and recognition for measuring consumer satisfaction: an application of affective computing.Information Technology and Management, 13(4), 321-332. [107] Rong, J., Li, G., & Chen, Y. P. (2009). Acoustic feature selection for automatic emotion recognition from speech. Information Processing & Management, 45(3), 315-328. [108] Royse, C. F., Chung, F., Newman, S., Stygall, J., & Wilkinson, D. J. (2013). Predictors of patient satisfaction with anaesthesia and surgery care: a cohort study using the Postoperative Quality of Recovery Scale. European Journal of Anaesthesiology (EJA), 30(3), 106-110. [109] Rummelhart, D. E. (1986). Learning representations by back-propagating errors.Nature, 323(9), 533-536. [110] Russell, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110(1), 145-172. [111] Sabharwal, N., Soch, H., & Kaur, H. (2010). Are we satisfied with incompetent services? A scale development approach for service recovery. Journal of Services Research, 10(1), 125-142. [112] Saco, R. M., & Goncalves, A. P. (2008). Service design: An appraisal. Design Management Review, 19(1), 10-19. [113] Saffer, D. (2005). The Role of Metaphor in Interaction Design. [114] Saffer, D. (2010). Designing for interaction: Creating smart applications and clever devices, New Riders Pub. [115] Shneiderman, B. (2000). The limits of speech recognition. Communications of the ACM, 43(9), 63-65 [116] Smith, A. K., & Bolton, R. N. (2002). The effect of customers'' emotional responses to service failures on their recovery effort evaluations and satisfaction judgments. Journal of the Academy of Marketing Science, 30(1), 5-23. [117] Spohrer, J., & Kwan, S. K. (2008). Service science, management, engineering, and design (SSMED): Outline & references. The Future of Services: Trends and Perspectives, Vol. 1,107-232. [118] Spohrer, J., Anderson, L., Pass, N., & Ager, T. (2008). Service science and service-dominant logic. Otago Forum, Vol. 2, 4-18. [119] Spreng, R. A., Harrell, G. D., & Mackoy, R. D. (1995). Service recovery: Impact on satisfaction and intentions. Journal of Services Marketing, 9(1), 15-23. [120] Tao, J., & Tan, T. (2005). Affective computing: A review. Affective computing and intelligent interaction, (pp. 981-995) Springer. [121] Tax, S. S., & Brown, S. W. (2012). Recovering and learning from service failure. Sloan Management. [122] Thomassey, S., & Fiordaliso, A. (2006). A hybrid sales forecasting system based on clustering and decision trees. Decision Support Systems, 42(1), 408-421. [123] Vargo, S. L., Maglio, P. P., & Akaka, M. A. (2008). On value and value co-creation: A service systems and service logic perspective. European Management Journal, 26(3), 145-152. [124] Vargo, Stephen L. and Robert F. Lusch (2006). Service-Dominant Logic: What it is, What it is not, What it might be. The Service-Dominant Logic of Marketing: Dialog, Debate, and Directions, 43-56. [125] Vergin, R., & O''Shaughnessy, D. (1995). Pre-emphasis and speech recognition. Electrical and Computer Engineering, Vol. 2, 1062-1065. [126] Vergin, R., O''Shaughnessy, D., & Gupta, V. (1996). Compensated mel frequency cepstrum coefficients. Acoustics, Speech, and Signal Processing, IEEE International Conference on, Vol. 1, 323-326. [127] Vesterinen, E. (2001). Affective computing. Digital Media Research Seminar, Helsinki, [128] Wang, C., Miao, Z., & Meng, X. (2008). Differential mfcc and vector quantization used for real-time speaker recognition system. Image and Signal Processing, Vol. 5, 319-323. [129] Wan-I, L., Chia-Chi, L., Cheng-Wu, C., & Chieh-Shan, C. (2012). An experimental design of service failure, recovery and speed analysis in cloud service. African Journal of Business Management, 6(8), 3059-3064. [130] Weiss, S., & Kulikowski, C. (1991). Computer systems that learn. [131] Weng, Z., Li, L., & Guo, D. (2010). Speaker recognition using weighted dynamic MFCC based on GMM. Anti-Counterfeiting Security and Identification in Communication (ASID), 2010 International Conference on, 285-288. [132] Wieland, H., Polese, F., Vargo, S. L., & Lusch, R. F. (2012). Toward a service (eco) systems perspective on value creation. International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 3(3), 12-25. [133] Wirtz, J., & Mattila, A. S. (2004). Consumer responses to compensation, speed of recovery and apology after a service failure. International Journal of Service Industry Management, 15(2), 150-166. [134] Wirtz, J., & McColl-Kennedy, J. R. (2010). Opportunistic customer claiming during service recovery. Journal of the Academy of Marketing Science, 38(5), 654-675. [135] Wu, X., Kumar, V., Quinlan, J. R., Ghosh, J., Yang, Q., Motoda, H., Philip, S. Y. (2008). Top 10 algorithms in data mining. Knowledge and Information Systems, 14(1), 1-37. [136] Yacoub, J., Takahashi, K., & Nakatsu, R. (2000). Emotion recognition in speech using neural networks. Neural Computing & Applications, 9(4), 290-296. [137] Yacoub, S. M., Simske, S. J., Lin, X., & Burns, J. (2003). Recognition of emotions in interactive voice response systems. Interspeech. [138] Yao, X. (1999). Evolving artificial neural networks. Proceedings of the IEEE, 87(9), 1423-1447. [139] Yu, F., Chang, E., Xu, Y., & Shum, H. (2001). Emotion detection from speech to enrich multimedia content. Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing, Vol. 1, 550-557. [140] Zeithaml, V. A., Parasuraman, A., & Berry, L. L. (1985). Problems and strategies in services marketing. The Journal of Marketing, 49(2), 33-46. [141] Zemke, R., & Bell, C. (1990). Service recovery: Doing it right the second time. Training, 27(6), 42-48. [142] Zheng, F., Zhang, G., & Song, Z. (2001). Comparison of different implementations of MFCC. Journal of Computer Science and Technology, 16(6), 582-589. [143] Zhou, X., He, X., & Chen, B. (2002). Genetic algorithm based on new evaluation function and mutation model for training of BPNN. Tsinghua Science and Technology, 7(1), 28-31.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/102392
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Témata: 物件導向技術, 繪圖程式庫, Object-Oriented technique, Graphic Library, 3D, OpenGL, JOGL
Relation: [1] Donald Hearn and M. Pauline Baker, “Computer Graphics with OpenGL, Third Edition”, Prentice Hall , 2003. [2] OpenGL.org , OpenGL, http://www.opengl.org, 1997 [3] Richard S Wright, Jr and Michael Sweet, OpenGL SuperBible, Second Edition, Waite Group, 1999 [4] Dennis J Bouvier, Getting Started with the Java 3D API, Sun Microsystems, 2009 [5] Grady Booch, Robert A. Maksimchuk, Michael W. Engle, Bobbi J. Young, Ph.D., Jim Conallen, Kelli A. Houston, Object-Oriented Analysis and Design with Applications, Addison Wesley, 2007 [6] Dave Shreiner (Author), The Khronos OpenGL ARB Working Group, OpenGL Programming Guide: The Official Guide to Learning OpenGL, Versions 3.0 and 3.1 (7th Edition), Addison Wesley, 2007 [7] Jim X. Chen, Edward J. Wegman, Foundations of 3D Graphics Programming Using JOGL and Java3D (Second Edition), Springer, 2008 [8] James D. Foley, Andries van Dam, Steven K. Feiner, John F. Hughes, Computer Graphics: Principles and Practice in C (2nd Edition), Addison Wesley, 1997 [9] OpenGL Architecture Review Board, Dave Shreiner, OpenGL Reference Manual: The Official Reference Document to OpenGL, Version 1.4 (4th Edition), Addison Wesley, 2004 [10] Edward Angel, Interactive Computer Graphics: A Top-Down Approach using OpenGL (4th Edition), Addison Wesley, 2006 [11] 向賢偉, 《以OpenGL建構的3D導覽系統》, 碩士論文, 淡江大學資訊管理研究所, 2008 [12] 劉定衡,《全尺度宇宙儀》, 碩士論文, 淡江大學資訊管理研究所, 2009 [13] 張弘毅,《支援遠近效果的繪圖程式庫》, 碩士論文, 淡江大學資訊管理研究所, 2010 [14] JogAmp.org , Java OpenGL, http://jogamp.org/, 2011 [15] Oracle.com , Java SE Desktop Technologies, http://www.oracle.com/technetwork/java/javase/tech/index-jsp-138252.html, 2011; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/77419
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Témata: 資通安全治理, 個案研究, IT治理, Information Security Governance, Case Study, IT Governance
Popis souboru: 143 bytes; application/octet-stream
Relation: [1] 行政院科技顧問組，"資安推動發展政策整合研究－資安治理機制與資安建設持續發展規劃"，2007，頁7-43。 [2] 行政院資通安全會報，"資通安全發展趨勢威脅及防護"，2007，頁17-26。 [3] 吳芝嫻，"以公司治理角度探討企業財務危機相關因素之研究"，2005，頁6-7。 [4] 吳琮璠，"資訊管理個案研究方法"，資訊管理學報，第四卷，第一期，1997，頁7-17。 [5] 姚俊羽，"能力成熟度整合模式之導入─以文件管理系統為例"，銘傳大學資訊管理研究所，2004，頁35-40。 [6] 孫強，"資通安全治理"，中國資訊系統審計與控制專業委員會，2004，頁5-10。 [7] 梁定澎，"資訊管理研究方法總論"，資訊管理學報，1997，第四卷，第一期，頁1-6。 [8] 陳姿伶，"個案研究法"，中興大學農業推廣教育研究所，2005，台中，頁2-7。 [9] 陳萬淇，個案研究法，華泰書局出版，1985。 [10] 陳瑞祥，"資訊安全治理白皮書談內控機制─董事會與高層應全面主導"， http://www.isecutech.com.tw/feature/view.asp?fid=375，2003。 [11] 黃俊英，"行銷研究"，華泰書局出版，1997，頁45-72。 [12] 黃國欽，"公部門資訊安全管理"，高雄第一科技大學資管系，2006，高雄，頁7-43。 [13] 羅千益，"資訊工程導論"，http://neuron.csie.ntust.edu.tw/homework/93/csie_introduction/homework3/B9315045/cmmiint.htm，2008/5。 [14] Allen, J. H., and Westby, J. R., "Characteristics of Effective Security Governance," EDPACS, Vol. XXXV, No. 5, 2007. [15] Andersen, P. W., "Information Security Governance," Information Security Technical Report, Vol. 6, No. 3, 2001, pp. 60-70. [16] Corporate Governance Task Force, "Information Security Governance - a Call to Action," Corporate Governance Task Force Report, April 2004. [17] Entrust, "Information Security Governance (ISG): an essential element of corporate governance," 2004, pp. 1-13. [18] Fujitsu, "Information Security Solutions," http://www.fujitsu.com/downloads/MAG/vol43-2/paper04.pdf, December 2006. [19] Information Technology Governance Institute, "Board Briefing on IT Governance 2nd Edition," 2003. [20] Information Technology Governance Institute, "Information Security Governance: Guidance for Boards of Directors and Executive Management 2nd Edition," 2006. [21] Institute of Internal Auditors, "Information Security Management and Assurance: A Call to Action for Corporate Governance," 2000. [22] Ministry of Economy, "Trade and Industry. Information Security Governance in Japan," September 2005. [23] Moulton, R., and Coles, R. S., "Applying Information Security Governance," Computer & Security, Vol.22, No.7, 2003, pp. 580-584. [24] Poore, R. S., "Information Security Governance," EDPACS, Vol. XXXIII, No. 5, 2005. [25] Posthumus, S., and Von Solms, R., "A framework for the governance of information security," Computers and Security, Vol.23, No.8, 2004, pp. 638-646. [26] Swindle, O., and Conner, B., "The Link between Information Security and Corporate Governance," http://www.computerworld.com/securitytopics/security/story/0,,92915,00.html?SKC=security-92915, 2004. [27] Von Solms, B., "Information Security governance: COBIT or ISO 17799 or both," Computers and Security, Vol. 24, No.2, 2005, pp. 99-104. [28] Von Solms, R., and Von Solms, S. H., "Information Security Governance: A model based on the Direct-Control Cycle," Computer & Security, Vol.26, No.6, 2006, pp. 408-412. [29] Von Solms, R., and Von Solms, S. H., "Information security governance: Due care," Computer & Security, Vol.25, No.7, 2006, pp. 494-497. [30] Von Solms, S. H., "Information Security Governance- Compliance management vs. operational management," Computer & Security, Vol.24, No.6, 2005, pp. 443-447. [31] Yin, R. K., "Case Study Research：Designs and Methods 2nd Edition," U.S.A., SAGE, 1994.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/34142; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/34142/1/
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Témata: IT治理, 資通安全治理, 資通安全治理成熟度, IT Governance, Information Security Governance, Information Security Governance Maturity
Popis souboru: 143 bytes; application/octet-stream
Relation: [1] 行政院科技顧問組，“行政院所屬各機關建立資通安全治理制度施行計畫(草案)說明”，2007，頁3-4。 [2] 行政院研考會，“資安人力調查及需求推估報告”，2007。 [3] 行政院科技顧問組，“資安推動發展政策整合研究－資安治理機制與資安建設持續發展規劃”，2007。 [4] 行政院國家資通安全會報綜合規劃組，“資通安全政策白皮書說明”，2007，頁1-6。 [5] 行政院研考會，“我國政府資通安全應用調查報告”，2006。 [6] 行政院研考會，“施政計畫與績效管理制度”， www.rdec.gov.tw/public/Attachment/52115114471.ppt，2004/5。 [7] 行政院研考會，“風險管理作業手冊”，2005/10，頁1-2。 [8] 行政院，“風險管理推動方案”， http://www.rdec.gov.tw/public/Attachment/6112314442671.doc，2005/8。 [9] 邱憶惠，“個案研究法：質化取向”，國立高雄師範大學教育學系教育研究，第7期，1999，頁113-127。 [10] 孫強，資通安全治理，中國資訊系統審計與控制專業委員會，2004。 [11] 孫強、郝亞斌、郝曉玲、孟秀轉，“IT治理：中國信息化發展的必由之路”，http://www.ccidnet.com，2004。 [12] 張紹勳，“研究方法”，滄海書局，2004，頁285-305。 [13] 陳瑞祥，“資訊安全治理白皮書談內控機制－董事會與高層應全面主導”， http://www.isecutech.com.tw/feature/view.asp?fid=375，2003。 [14] 黃國欽，“公部門資訊安全治理”，國立高雄第一科技大學資管所碩士論文，2006/1。 [15] 高凱聲，“新通訊科技帶來的資安挑戰與防範”， www.informationsecurity.com.tw/seminar/FY2006/pdf/Keynote%204.pdf. [16] 潘慧玲，“教育研究的取徑：概念與應用”，高等教育出版，2003，頁199-228。 [17] Allen, J. H., Westby, J. R., “Characteristics of Effective Security Governance,” EDPACS, Vol. XXXV, No. 5, 2007. [18] Andersen, P. W., “Information Security Governance,” Information Security Technical Report, Vol. 6, No. 3, 2001, pp. 60-70. [19] Benbasat, I., Goldstein, D. and Mead M., “The Case Research in Studies of Information System,” MIS Quarterly, Vol. 11, No. 3, 1987, pp. 369-386. [20] Corporate Governance Task Force, “Information Security Governance: A Call to Action,” Corporate Governance Task Force Report, April 2004. [21] ESCAP, “What is Good Governance,” http://www.unescap.org/pdd/prs/ProjectActivities/Ongoing/gg/governance.asp. [22] European Commission, “European Governance - A White Paper,” July 2001. [23] European Commission, “Governance,” http://ec.europa.eu/governance/index_en.htm, 2007. [24] ITGI, “Board Briefing on IT Governance 2nd Edition,” 2003. [25] ITGI, “Information Security Governance: Guidance for Boards of Directors and Executives Management 2nd Edition,” 2006. [26] Ministry of Economy, Trade and Industry, “Information Security Governance in Japan,” September 2005. [27] Moulton, R., Coles, R. S., “Applying Information Security Governance,” Computers & Security, Vol. 22, No. 7, 2003, pp. 580-584. [28] NIST, “Information Security Handbook: A Guide for Managers,” October 2006. [29] Poole, V., “Why Information Security Governance Is Critical to Wider Corporate Governance Demands- A European Perspective,” Information Systems Control Journal, Vol. 1, 2006, pp. 23-25. [30] Poore, R. S., “Information Security Governance,” EDPACS, Vol. XXXIII, No. 5, 2005. [31] Posthumus, S., Von Solms, R., “A framework for the governance of information security,” Computers & Security, Vol. 23, 2004, pp. 638-646. [32] The World Bank, “ What is our approach to governance,” http://web.worldbank.org/. [33] Van Grembergen, W., “Introduction to the Minitrack IT Governance and its Mechanisms,” Proceedings of the 38th Hawaii International Conference on System Sciences, 2005. [34] Von Solms, R., Von Solms S. H., “Information Security Governance: Due Care,” Computers & Security, Vol. 25, 2006, pp. 494-497. [35] Webb, P., Pollard, C. and Ridley, G., “Attempting to define IT Governance: Wisdom or Folly,” Proceedings of the 39th Hawaii International Conference on System Sciences, 2006. [36] Whitman, M. E., Mattford, H. J., “Principles of Information Security,” Course Technology, 2003. [37] Wikipedia, “Information Security Governance,” http://en.wikipedia.org/wiki/Information_Security_Governance; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/34148; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/34148/1/
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Témata: 自動摘要, TFIDF, 相似度, Hownet, 重複句排除, Automatic Summarization, Similarity Measure, Duplicate Sentences
Popis souboru: 143 bytes; application/octet-stream
Relation: [1] CKIP Autotag 中央研究院詞庫小組，取自http://godel.iis.sinica.edu.tw/CKIP/ws，2003。 [2] 王永成、劉功申、劉傳漢、胡佩華、孫展，“論文本的自動摘要”，上海交通大學電腦科學技術系，2000。 [3] 李彬、劉挺、秦兵、李生，“基於語義依存的漢語句子相似度計算”，哈爾濱工業大學信息檢索研究室論文，2003。 [4] 徐銘忠，“植基於本體論之文件摘要系統之研究－以中文股市新聞為例”，東海大學資訊工程與科學系碩士論文，2004。 [5] 陳世偉，“植基於功能詞及知網架構之軟體搜尋系統”，淡江大學資訊管理學系碩士論文，2004。 [6] 陳光華，“網際網路服務的過去現在與未來”，國立成功大學圖書館館刊，6，1-7，2000。 [7] 曾元顯，“中文手機新聞簡訊自動摘要”，第十六屆自然語言與語音處理研討會，台北，頁177-189，2004年9月2-3日。 [8] 楊存一、邱立豐，“TFIDF與GBP方法於重要句子擷取績效評估”，雲林科技大學資訊管理學系碩士論文，2001。 [9] 董振東、董強，知網，取自http://keenage.com，1999。 [10] 劉政璋、葉鎮源，“以概念分群為基礎之新聞事件自動摘要”，交通大學資訊科學系碩士論文，2005。 [11] 劉群、李建素，“基於知網的詞彙語義相似度計算”，第三屆漢語詞彙語義研討會，2001。 [12] 謝文泰、陳文鋕、張履平，“以句子資訊量來產生文件摘要之模式”，第七屆人工智慧與應用研討會(TAAI2002)論文集，C4-7，台北，2002。 [13] Chen, F., Han, K. and Chen, G., "An Approach to Sentence-Selection-Based Text Summarization", IEEE Region 10 Conference on Computers, Communications, Control and PowerEngineering, (TENCON ''02) Volume1, Page(s):489-493, Oct. 2002. [14] Edmundson, H.P., "New methods in automatic abstracting extracting", Journal of the Association for Computing Machinery, 16(2):264-285, 1969. [15] Johns, K.S., "A Statistical Interpretation of Term Specificity and its Application in Retrieval", Journal of Documentation, 28(1): 11-20, March 1972. [16] Larocca-Neto, J., Freitas, A.A. and Kaestner, C.A. A., "Automatic Text Summarization using a Machine Learning Approach", In Proceedings of 16th Brazilian Symposium on Artificial Intelligence, 2002:205-215, 2002. [17] Luhn, H.P., "The Automatic Creation of Literature Abstracts", IBM Journal of Research and Development, 2(2):159-165, 1958. [18] Mani, I. and Bloedorn, E., "Machine Learning of Generic and User-focused Summarization", In Proceedings of Fifteenth National Conference on Artificial Intelligence, AAAI-98:821-826, 1998. [19] McDonald, D. and Chen, H.C., "Using Sentence-Selection Heuristics to Rank Text Segment in TXTRACTOR", Proceedings of the second ACM/IEEE-CS joint conference on Digital libraries Portland, Oregon, USA, Page(s): 28-35, 2002. [20] Ohsawa, Y., Benson, N. E. and Yachida, M., "KeyGraph: Automatic Indexing by Co-occurrence Graph based on Building Construction Metaphor", Proceedings of Advanced Digital Library Conference, 1998.; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/34098; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/34098/1/
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Témata: 向量空間模式, 文章表現法, 自動推薦, 論文審查者, OpenConf推薦模式, Vector Space Model, Document Representation, Automatic Recommendation, Paper Reviewer, OpenConf Recommendation Model
Popis souboru: 143 bytes; application/octet-stream
Relation: [1]中央研究院詞庫小組， AutoTag ，http://godel.iis.sinica.edu.tw/CKIP/ws/，2003。 [2]邱炯友，李怡萍，學術電子期刊編輯整合平台市場與個案：以教育資料與圖書館學季刊為例，教育資料與圖書館學，第 43 卷第 3 期．頁 327 – 345，2006。 [3]劉群，李素建，基於《知網》的辭彙語義相似度計算，中文計算語言學期刊，第 7 卷第 2 期, 頁 59-76，2002 [4]顏玉茵，台灣期刊電子化評閱系統之評析，南華大學碩士論文，頁19-24，2004。 [5]Aas, K. and Eikvil, L., “Text Categorisation: A Survey,” Technical Report, Norwegian Computing Center, June 1999. [6]Allan, J., Topic Detection and Tracking: Event-based Information Organization, Kluwer Academic Publishers, 2002. [7]Baeza-Yates, R. and Ribeiro-Neto, B., Modern Information Retrieval, Addsion Wesley Longman Limited, 1999. [8]Chakrabarti, S., Mining the Web: Discovering Knowledge from Hypertext Data, Morgan Kaufmann, 2003. [9]Kondrak, G., Marcu, D. and Knight, K., “Cognates Can Improve Statistical Translation Models,” Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, pp. 46-48, 2003. [10]Salton, G. and Buckley, C., “Term-Weighting Approaches in Automatic Retrieval,” Information Processing and Management, vol. 24, no. 5, pp. 513-523, 1988. [11]Salton, G. and McGill, M. J., Introduction to Modern Information Retrieval, McGraw-Hill, 1989. [12]van Rijsbergen C. J., Information Retrieval, London: Butterworths , 1979. [13]Ware, M., Online Submission and Peer Review Systems, Learned Publishing, 2005. [14]Zakon Group, OpenConf, http://www.zakongroup.com/technology/openconf.shtml; https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/34108; https://tkuir.lib.tku.edu.tw/dspace/bitstream/987654321/34108/1/
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