The Research of E-Commerce Personalized Recommendation

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Abstract:

With the rapid development of electronic commerce, the problem of "information overload" leads to the difficulty that user can't search the required goods effectively , personalized recommendation technology has been applied in e-commerce and popularization. By using the method of qualitative analysis of the current e-commerce site,the paper compare the information retrieval, association rule, content-based filtering and collaborative filtering four main recommendation technologies and analysis the advantages and disadvantages in the application layer, the recommendation technologies are introduced to review e-commerce research hot topic in the field of personalized recommendation, and analysis the current domestic e-commerce personalized recommendation theory research and application status, finally propose the challenges faced by e-commerce personalized recommendation domain.

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6762-6765

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May 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] MICHAEL O, NEIL H, NICHOLAS K, et al. Collaborative recommendation: a robustness analysis [A] . ACM Transactions on Internet Technology, Special Issue of Machine Learning for the Internet [C]. (2002).

Google Scholar

[2] ADOMAVICIUS G, T UZHILIN A. Extending recommender systems: a multidimensional approach [ A] . Proceedings of the Fifth ACM Conference on Digital Libraries [C]. 2001. 115 -123.

Google Scholar

[3] RAYID G, ANDRES F. Building recommender systems using a knowledge based of product semantics [ R] . Chicago: Accenture Technology Labs, (2001).

Google Scholar

[4] Soto-A costa P, A L. Analyzing e-business value creation from a resource-based perspective[J]. International Journal o f Information Management, 2008, 28(1): 49- 60.

DOI: 10.1016/j.ijinfomgt.2007.05.001

Google Scholar

[5] MalhotraA, Gosain S, E Saw O A. Absorptive capacity con figurations in supply cha ins: Gear ing for partner-enabled market know ledge creation[J]. M IS Quarterly, 2005, 29( 1): 145- 187.

DOI: 10.2307/25148671

Google Scholar

[6] Chae B S, Yen H J R, Sheu C. Information technology and supply cha in collaboration: Moderating effects of existing relationships between partners[J]. IEEE Transactions on Engineering Management, 2005, 52( 4): 440- 448.

DOI: 10.1109/tem.2005.856570

Google Scholar