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下一代移动推荐系统

宋乐怡 熊辉 张蓉

宋乐怡, 熊辉, 张蓉. 下一代移动推荐系统[J]. 华东师范大学学报(自然科学版), 2013, (3): 37-45.
引用本文: 宋乐怡, 熊辉, 张蓉. 下一代移动推荐系统[J]. 华东师范大学学报(自然科学版), 2013, (3): 37-45.
SONG Le-yi, XIONG Hui, ZHANG Rong. Towards the next generation of mobile recommender systems[J]. Journal of East China Normal University (Natural Sciences), 2013, (3): 37-45.
Citation: SONG Le-yi, XIONG Hui, ZHANG Rong. Towards the next generation of mobile recommender systems[J]. Journal of East China Normal University (Natural Sciences), 2013, (3): 37-45.

下一代移动推荐系统

详细信息
  • 中图分类号: TP391

Towards the next generation of mobile recommender systems

  • 摘要: 推荐系统的目的是通过利用用户的评价信息,实现从过载的信息中识别出用户感兴趣的内容.移动环境下的空间数据复杂性较高,并且用户的上下文信息更加模糊,从而使得移动个性化推荐相比于传统领域面临更大的挑战.本文通过介绍传统推荐算法和移动环境下个性化推荐的特性,给出了移动推荐的挑战;在基于GPS信息的出租车线路推荐和旅游包推荐两个移动案例基础上,提出了移动序列推荐问题及基于约束的旅游推荐问题,并给出了相应的解决方案.
  • [1] [1] GE Y, XIONG H, TUZHILIN A, et al. Anenergy-efficient mobile recommender system[C]//Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data mining. Washington DC: ACM, 2010: 899-908.

    [2] HOSSEINI-POZVEH M, NEMATBAKHSH M, MOVAHHEDINIA N. A Multidimensional Approach for Context-aware Recommendation in Mobile Commerce [J]. International Journal of Computer Science and Information Security, 2009, 3(1): 86-91.

    [3] YANG W S, CHENG H C, DIA J B. A location-aware recommender system for mobile shopping environments[J]. Expert Systems with Applications, 2008, 34(1): 437-445.

    [4] GEDIMINAS A, ALEXANDER T. Towards the next generation of recommender systems: A survey of the state-of-the-art and possible extensions [J]. IEEE Transactions on Knowledge and Data Engineering, 2005, 17(6): 734-749.

    [5] 许海玲, 吴潇, 李晓东,等. 互联网推荐系统比较研究[J]. 软件学报, 2009, 20(2): 350-362.

    [6] 徐风苓, 王立才, 孟祥武. 基于移动用户上下文相似度的协同过滤推荐算法[J]. 电子与信息学报, 2011, 33(11): 2785-2789.

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    [8] MOONEY R J, ROY L. Content-based book recommending using learning for text categorization[C]//Proceedings of the SIGIR-99 Workshop on Recommender Systems:Algorithms and Evaluation. Berkeley,CA: ACM, 1999.

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    [14] ROBERTSON S. Threshold setting and performance optimization in adaptive filtering[J]. Information Retrieval, 2002, 5: 239-256.

    [15] ZHANG Y, CALLAN J. Maximum likelihood estimation for filtering thresholds[C]//Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval. New Orleans, LA, USA: ACM Press, 2001: 294-302.

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    [17] BURKE R. Hybrid recommender systems: Survey and experiments [J]. User Modeling and User-adapted Interaction, 2002, 12(4): 331-370.

    [18] 王立才, 孟祥武, 张玉洁. 上下文感知推荐系统[J]. 软件学报, 2012, 23(1): 1-20.

    [19] SOBOROFF I, NICHOLAS C. Combining content and collaboration in text filtering[C]//Proceedings of the IJCAI’99 Workshop:Machine Learning for Information Filtering, 1999.

    [20] GE Y, LIU Q, XIONG H, et al. Cost-aware Travel Tour Recommendation[C]//Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining. San Diego, California, USA: ACM Press, 2011: 983.

    [21] CENA F, CONSOLE L, GENA C, et al. Integrating heterogeneous adaptation techniques to build a flexible and usable mobile tourist guide[J]. AI Communications, 2006, 19(4): 369-384.

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    [25] CHEVERST K, DAVIES N, MITCHELL K. Developing a context-aware electronic tourist guide: some issues and experiences[C]//Proceedings of the SIGCHI conference on Human factors in computing systems. The Hague, Netherlands: ACM Press, 2000: 17-24.

    [26] AVERJANOVA O, RICCI F, NGUYEN Q N. Map-Based Interaction with a Conversational Mobile Recommender System[C]//The Second International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies. IEEE, 2008: 212-218.

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  • [1] 吴威, 李彩霞, 陈雪初.  基于生态系统服务的海岸带生态修复工程成效评估 . 华东师范大学学报(自然科学版), 2020, (3): 98-108. doi: 10.3969/j.issn.1000-5641.201941027
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出版历程
  • 收稿日期:  2013-03-01
  • 修回日期:  2013-04-01
  • 刊出日期:  2013-05-25

下一代移动推荐系统

  • 中图分类号: TP391

摘要: 推荐系统的目的是通过利用用户的评价信息,实现从过载的信息中识别出用户感兴趣的内容.移动环境下的空间数据复杂性较高,并且用户的上下文信息更加模糊,从而使得移动个性化推荐相比于传统领域面临更大的挑战.本文通过介绍传统推荐算法和移动环境下个性化推荐的特性,给出了移动推荐的挑战;在基于GPS信息的出租车线路推荐和旅游包推荐两个移动案例基础上,提出了移动序列推荐问题及基于约束的旅游推荐问题,并给出了相应的解决方案.

English Abstract

宋乐怡, 熊辉, 张蓉. 下一代移动推荐系统[J]. 华东师范大学学报(自然科学版), 2013, (3): 37-45.
引用本文: 宋乐怡, 熊辉, 张蓉. 下一代移动推荐系统[J]. 华东师范大学学报(自然科学版), 2013, (3): 37-45.
SONG Le-yi, XIONG Hui, ZHANG Rong. Towards the next generation of mobile recommender systems[J]. Journal of East China Normal University (Natural Sciences), 2013, (3): 37-45.
Citation: SONG Le-yi, XIONG Hui, ZHANG Rong. Towards the next generation of mobile recommender systems[J]. Journal of East China Normal University (Natural Sciences), 2013, (3): 37-45.
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