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Issue 3
Jul.  2013
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YU Wen-zhe, ZHANG Rong, WANG Li. Recommendation in E-commerce[J]. Journal of East China Normal University (Natural Sciences), 2013, (3): 46-53.
Citation: YU Wen-zhe, ZHANG Rong, WANG Li. Recommendation in E-commerce[J]. Journal of East China Normal University (Natural Sciences), 2013, (3): 46-53.

Recommendation in E-commerce

  • Received Date: 2013-03-01
  • Rev Recd Date: 2013-04-01
  • Publish Date: 2013-05-25
  • For e-commerce sites, in order to promote the development and win more benefits, attracting and keeping the customers becomes very important. One of the most useful technologies is recommendation algorithms. In e-commerce sites, sidebar advertising is a common form of recommendation, which can be divided into three main categories: content-based, collaborative filtering and hybrid recommendation algorithms. However, current recommendation algorithms are challenged by new application requirements, such as diversification, personalization, intelligentization and timeliness. It is urgent to design new algorithms to meet these requirements.
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  • [1]
    [1] WEN H J, CHEN H G, HWANG H G. E-commerce web site design: strategies and models[J]. Information Management & Computer Security, 2001, 9(1): 5-12.

    [2] ARENS W F. 当代广告学[M]. 8版.北京:人民邮电出版社, 2006.

    [3] EBAY. Online Retail Media[EB/OL]. 2012. http://www2.ebayadvertising.com/uk/online-retail-media.

    [4] HABEGGER J. Why Amazon is about to Become a Force in Online Advertising[EB/OL]. 2011. http://www.commercialalert.org/issues/culture/internet-socialmedia/why-amazon-is-about-to-become-a-force-in-online-advertising.

    [5] O’REILLY T. The Convergence of Advertising and E-Commerce[EB/OL]. 2010. http://radar.oreilly.com/2010/02/convergence-advertising-mobile-ecommerce.html.

    [6] SCHAFER J B, KONSTAN J, RIEDI J. Recommender systems in e-commerce[C]. Proceedings of the 1st ACM conference on Electronic commerce, 1999: 158-166.

    [7] ADOMAVICIUS G, TUZHILIN A. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions[J]. Knowledge and Data Engineering, 2005, 17(6): 734-749.

    [8] BAEZA-YATES R, RIBEIRO-NETO B. Modern Information Retrieval[M]. [S.l.] Addison-Wesley, 1999.

    [9] MOONEY R J, ROY L. Content-based book recommending using learning for text categorization[C]. Proceedings of the fifth ACM conference on Digital libraries, 2000: 195-204.

    [10] GOLDBERG D, NICHOLS D, OKI B M, et al. Using collaborative filtering to weave an information tapestry[J]. Communications of the ACM, 1992, 35(12): 61-70.

    [11] RESNICK P, IACOVOU N, SUCHAK M, et al. GroupLens: an open architecture for collaborative filtering of netnews[C]. Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work, 1994: 175-186.

    [12] SHARDANAND U, MAES P. Social information filtering: algorithms for automating “word of mouth”[C]. Proceedings of the SIGCHI conference on Human Factors in Computing Systems, 1995: 210-217.

    [13] LINDEN G, SMITH B, YORK J. Amazon.com recommendations: item-to-item collaborative filtering[J]. Internet Computing, IEEE, 2003, 7(1): 76-80.

    [14] NETFLIX. The Netflix Prize[EB/OL]. 2009. http://www.netflixprize.com.

    [15] RODGERS J L, NICEWANDER W A. Thirteen ways to look at the correlation coefficient[J]. American Statistician, 1988, 42(1): 59-66.

    [16] BREESE J S, HECKERMAN D, KADIE C. Empirical analysis of predictive algorithms for collaborative filtering[C]. Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998: 43-52.

    [17] DESHPANDE M, KARYPIS G. Item-based top-N recommendation algorithms[J]. ACM Transactions on Information Systems, 2004, 22(1): 143-177.

    [18] CLAYPOOL M, GOKHALE A, MIRANDA T, et al. Combining content-based and collaborative filters in an online newspaper[C]. Proceedings of ACM SIGIR Workshop on Recommender Systems: Algorithms and Evaluation, 1999.

    [19] BALABANOVIC M, SHOHAM Y. Fab: content-based, collaborative recommendation[J]. Communications of the ACM, 1997, 40(3): 66-72.

    [20] BASU C, HIRSH H, COHEN W. Recommendation as classification: using social and content-based information in recommendation[C]. Proceedings of the 15th national/10th conference on Artificial Intelligence/Innovative Applications of Artificial Intelligence, 1998: 714-720.

    [21] AGRAWAL R, GOLLAPUDI S, HALVERSON A, et al. Diversifying search results[C]. Proceedings of the Second ACM International Conference on Web Search and Data Mining, 2009.

    [22] ZIEGLER C N, MCNEE S M, KONSTAN J A, et al. Improving recommendation lists through topic diversification[C]. Proceedings of the 14th international conference on World Wide Web, 2005: 22-32.

    [23] YU C, LAKSHMANAN L, AMER-YAHIA S. It takes variety to make a world: diversification in recommender systems[C]. Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, 2009: 368-378.

    [24] BOIM R, MILO T, NOVGORODOV S. DiRec: Diversified recommendations for semantic-less Collaborative Filtering[C]. Proceedings of the 2011 IEEE 27th International Conference on Data Engineering, 2011: 1312-1315.

    [25] ADOMAVICIUS G, TUZHILIN A. Personalization technologies: a process-oriented perspective[J]. Communications of the ACM, 2005, 48(10): 83-90.

    [26] VAN DER HEIJDEN H, KOTSIS G, KRONSTEINER R. Mobile Recommendation Systems for Decision Making ‘On the Go’[C]. Proceedings of the International Conference on Mobile Business, 2005: 137-143.
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