과제정보
This work was supported by a grant from Kyung Hee University in 2013.(KHU-20130544)
참고문헌
- 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, 17(6), 734-749. https://doi.org/10.1109/TKDE.2005.99
- Aimeur, E., Brassard, G., Fernandez, J. M., Onana, F. S. M., and Rakowski, Z. (2008). Experimental Demonstration of a Hybrid Privacy-Preserving Recommender System. Proceedings of the Third International Conference on Availability, Reliability and Security, 161-170.
- Bandara, U. and Chen, J. (2011). Ubira: A Mobile Platform for an Integrated Online/offline Shopping Experience. Proceedings of the 13th International Conference on Ubiquitous computing, 547-548.
- Beath, C., Becerra-Fernandez, I., Ross, J., and Short, J. (2012). Finding Value in the Information Explosion. MIT Sloan Management Review, 53(4), 18-20.
- Beneke, J., de Sousa, S., Mbuyu, M., and Wickham, B. (2016). The effect of negative online customer reviews on brand equity and purchase intention of consumer electronics in South Africa. The International Review of Retail, Distribution and Consumer Research, 26(2), 171-201. https://doi.org/10.1080/09593969.2015.1068828
- Berkovsky, S., Eytani, Y., Kuflik, T., and Ricci, F. (2007). Enhancing Privacy and Preserving Accuracy of a Distributed Collaborative Filtering. Proceedings of the 2007 ACM conference on Recommender systems, 9-16.
- Dong-hui, Y. and Guang, Y. (2013). Bigger Data Set, Better Personalized Recommendation Performance? Proceedings of the 2013 International Conference on Management Science and Engineering, 28-35.
- Gbadamosi, A. (2009). Cognitive dissonance: The implicit explication in low-income consumers' shopping behaviour for "low-involvement" grocery products. International Journal of Retail and Distribution Management, 37(12), 1077-1095. https://doi.org/10.1108/09590550911005038
- Herlocker, J., Konstan, J., Terveen, L., and Riedl, J. (2004). Evaluating Collaborative Filtering Recommender Systems. ACM Transactions on Information Systems, 22(1), 5-53. https://doi.org/10.1145/963770.963772
- Huang, Z. (2007). Selectively acquiring ratings for product recommendation. Proceedings of the Ninth International Conference on Electronic Commerce, 379-388.
- Jannach, D., Zanker, M., Felfernig, A., and Friedrich, G. (2010). Recommender Systems: An Introduction. Cambridge University Press, New York.
- Ji, C., Li, Y., Qiu, W., Awada, U., and Li, K. (2012). Big Data Processing in Cloud Computing Environments. Proceedings of the 12th International Symposium on Pervasive Systems, Algorithms and Networks, 17-23.
- Kim, H.K., Jang, M.K., Kim, J.K., and Cho, Y.H. (2010). A New Item Recommendation Procedure using Preference Boundary. Asia Pacific Journal of Information Systems, 20(1), 81-99. https://doi.org/10.1111/j.1365-2575.2008.00311.x
- Kim, Y. and Srivastava, J. (2007). Impact of Social Influence in e-commerce Decision Making. Proceedings of the Ninth International Conference on Electronic Commerce, 293-302.
- Lee, Y. and Kwon, O. (2010). Information Privacy Concern in Context-Aware Personalized Services: Results of a Delphi Study. Asia Pacific Journal of Information Systems, 20(2), 63-86. https://doi.org/10.5859/KAIS.2011.20.3.63
- Leskovec, J. and Faloutsos, C. (2006). Sampling from large graphs. Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 631-636.
- Lockshin, L. S., Spawton, A. L., and Macintosh, G. (1997). Using product, brand and purchasing involvement for retail segmentation. Journal of Retailing and Consumer services, 4(3), 171-183. https://doi.org/10.1016/S0969-6989(96)00048-3
- McAuley, J., Pandey, R., and Leskovec, J. (2015). Inferring Networks of Substitutable and Complementary Products. Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 785-794.
- Michaelidou, N. and Dibb, S. (2008). Consumer involvement: a new perspective. The Marketing Review, 8(1), 83-99. https://doi.org/10.1362/146934708X290403
- Provost, F. and Fawcett, T. (2013). Data Science for Business: What you need to know about data mining and data-analytic thinking. O'Reilly Media, Inc., California.
- Sarwar, B., Karypis, G., Konstan, J., and Riedl, J. (2000). Analysis of Recommendation Algorithms for e-commerce. Proceedings of the 2nd ACM conference on Electronic commerce, 158-167.
- Sarwar, B., Karypis, G., Konstan, J., and Riedl, J. (2002). Recommender Systems for Large-scale e-commerce: Scalable Neighborhood Formation using Clustering. Proceedings of the fifth International Conference on Computer and Information Technology.
- Smith, B. and Linden, G. (2017). Two Decades of Recommender Systems at Amazon. com. IEEE Internet Computing, 21(3), 12-18. https://doi.org/10.1109/MIC.2017.72
- Smith, H.J., Milberg, S.J., and Burke, S.J. (1996). Information Privacy: Measuring Individuals' Concerns about Organizational Practices. MIS quarterly, 167-196.
- Zaki, M. J., Parthasarathy, S., Li, W., and Ogihara, M. (1997). Evaluation of Sampling for Data Mining of Association Rules. Proceedings of the Seventh International Workshop on Research Issues in Data Engineering, 42-50.