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基于动态时间的个性化推荐模型

谭黎立 聂瑞华 梁军 王进宏

谭黎立, 聂瑞华, 梁军, 王进宏. 基于动态时间的个性化推荐模型[J]. 华南师范大学学报(自然科学版), 2017, 49(3): 123-128.
引用本文: 谭黎立, 聂瑞华, 梁军, 王进宏. 基于动态时间的个性化推荐模型[J]. 华南师范大学学报(自然科学版), 2017, 49(3): 123-128.
Personalized Recommendation Model Based on Dynamic Time[J]. Journal of South China normal University (Natural Science Edition), 2017, 49(3): 123-128.
Citation: Personalized Recommendation Model Based on Dynamic Time[J]. Journal of South China normal University (Natural Science Edition), 2017, 49(3): 123-128.

基于动态时间的个性化推荐模型

基金项目: 

中移动基金项目;广州市科技和信息化局基金项目

详细信息
    通讯作者:

    谭黎立

Personalized Recommendation Model Based on Dynamic Time

  • 摘要: 在推荐系统中,往往会存在数据的非实时性、稀疏性和冷启动性等问题,文中通过引入遗忘曲线来跟踪用户对资源偏好程度随时间变化情况,利用提出一种改进的K-Means聚类算法对用户集进行聚类,根据改进的个性化推荐算法对用户进行推荐,建立了一种基于动态时间的个性化推荐模型. 通过实验验证,文中提出的个性化推荐模型能够获取准确的用户偏好信息,并缓解冷启动问题,降低算法计算的时间空间复杂度,提高个性化推荐算法的推荐质量.
  • [1]Li Chen, Personality in Recommender Systems[C]//Proceedings of the 3rd Workshop on Emotions and Personality in Personalized Systems 2015, p.2-2, September 16-20, 2015, Vienna, Austria
    [2]Maria Augusta S.N. Nunes, Rong Hu, Personality-based recommender systems: an overview[C]//Proceedings of the sixth ACM conference on Recommender systems, September 09-13, 2012, Dublin, Ireland.
    [3]Nirmal Jonnalagedda, Susan Gauch, Personalized News Recommendation Using Twitter[C]//Proceedings of the 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), p.21-25, November 17-20, 2013.
    [4]Ralf Krestel.Recommendation on the social web: diversification and personalization[J].Proceedings of the 2011 international workshop on DETecting and Exploiting Cultural diversiTy on the social web, 2011, 10(1):24-24
    [5]Yuan Guan.Preference of online users and personalized recommendations[J].Physica A: Statistical Mechanics and its Applications, 2013, 392(16):3417-3423
    [6]Mojtaba Salehi.Hybrid recommendation approach for learning material based on sequential pattern of the accessed material and the learner’s preference tree[J].Knowledge-Based Systems, 2013, 48(1):57-69
    [7]Yongfeng Zhang.Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis[C]//Proceedings of the 24th International Conference on World Wide Web, 2015, 1373-1383.
    [8] NAYAK R.A social matching system for an online dating network: a preliminary study[C]//Proceedings 2010 10th IEEE International Conference on Data Mining Workshops (ICDMW 2010). 2010.352-357.
    [9] WANG T T.Predicting New User’s Behavior in Online Dating Systems[M]. Advanced Data Mining and Applications.Springer Berlin Heidelberg, 2011.266-277.
    [10]于洪, 李俊华.一种解决新项目冷启动问题的推荐算法[J].软件学报, 2015, 26(6):1395-1408
    [11]Koren Y.Collaborative filtering with temporal dynamics[J].Communications of the ACM, 2010, 53(4):89-97
    [12]Florent Garcin.Personalized News Recommendation Based on Collaborative Filtering[C]//Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology, p.437-441, December 04-07, 2012.
    [13] 丁浩, 戴牡红.基于用户评分和遗传算法的协同过滤推荐算法[J].计算机工程与应用, 2015,51 (17): 0-1
    [14]Fidel Cacheda.Comparison of collaborative filtering algorithms: Limitations of current techniques and proposals for scalable, high-performance recommender systems[C]// ACM Transactions on the Web (TWEB), 2011, 1-33
    [15]Cataldo Musto.Enhanced vector space models for content-based recommender systems[C]//In Proceedings of the fourth ACM conference on Recommender systems, Rec Sys ‘10, pages 361-364, New York, NY, USA, 2010.ACM.
    [16]L Averell and A Heathcote.The form of the forgetting curve and the fate of memories[J].Journal of Mathematical Psychology, 2011, 55(1):25-35

    [1]Li Chen, Personality in Recommender Systems[C]//Proceedings of the 3rd Workshop on Emotions and Personality in Personalized Systems 2015, p.2-2, September 16-20, 2015, Vienna, Austria
    [2]Maria Augusta S.N. Nunes, Rong Hu, Personality-based recommender systems: an overview[C]//Proceedings of the sixth ACM conference on Recommender systems, September 09-13, 2012, Dublin, Ireland.
    [3]Nirmal Jonnalagedda, Susan Gauch, Personalized News Recommendation Using Twitter[C]//Proceedings of the 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), p.21-25, November 17-20, 2013.
    [4]Ralf Krestel.Recommendation on the social web: diversification and personalization[J].Proceedings of the 2011 international workshop on DETecting and Exploiting Cultural diversiTy on the social web, 2011, 10(1):24-24
    [5]Yuan Guan.Preference of online users and personalized recommendations[J].Physica A: Statistical Mechanics and its Applications, 2013, 392(16):3417-3423
    [6]Mojtaba Salehi.Hybrid recommendation approach for learning material based on sequential pattern of the accessed material and the learner’s preference tree[J].Knowledge-Based Systems, 2013, 48(1):57-69
    [7]Yongfeng Zhang.Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis[C]//Proceedings of the 24th International Conference on World Wide Web, 2015, 1373-1383.
    [8] NAYAK R.A social matching system for an online dating network: a preliminary study[C]//Proceedings 2010 10th IEEE International Conference on Data Mining Workshops (ICDMW 2010). 2010.352-357.
    [9] WANG T T.Predicting New User’s Behavior in Online Dating Systems[M]. Advanced Data Mining and Applications.Springer Berlin Heidelberg, 2011.266-277.
    [10]于洪, 李俊华.一种解决新项目冷启动问题的推荐算法[J].软件学报, 2015, 26(6):1395-1408
    [11]Koren Y.Collaborative filtering with temporal dynamics[J].Communications of the ACM, 2010, 53(4):89-97
    [12]Florent Garcin.Personalized News Recommendation Based on Collaborative Filtering[C]//Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology, p.437-441, December 04-07, 2012.
    [13] 丁浩, 戴牡红.基于用户评分和遗传算法的协同过滤推荐算法[J].计算机工程与应用, 2015,51 (17): 0-1
    [14]Fidel Cacheda.Comparison of collaborative filtering algorithms: Limitations of current techniques and proposals for scalable, high-performance recommender systems[C]// ACM Transactions on the Web (TWEB), 2011, 1-33
    [15]Cataldo Musto.Enhanced vector space models for content-based recommender systems[C]//In Proceedings of the fourth ACM conference on Recommender systems, Rec Sys ‘10, pages 361-364, New York, NY, USA, 2010.ACM.
    [16]L Averell and A Heathcote.The form of the forgetting curve and the fate of memories[J].Journal of Mathematical Psychology, 2011, 55(1):25-35
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出版历程
  • 收稿日期:  2016-03-28
  • 修回日期:  2016-06-18
  • 刊出日期:  2017-06-25

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