计算机科学 ›› 2017, Vol. 44 ›› Issue (2): 103-106.doi: 10.11896/j.issn.1002-137X.2017.02.014
• 2016 第十三届全国Web 信息系统及其应用学术会议 • 上一篇 下一篇
高发展,黄梦醒,张婷婷
GAO Fa-zhan, HUANG Meng-xing and ZHANG Ting-ting
摘要： 协作过滤推荐算法是推荐系统中应用最广泛的算法之一。通过分析传统协作过滤算法中由数据稀疏性导致的推荐精度不高的问题,在基于专家信任的协作过滤推荐算法的基础上,提出了一种综合用户特征及专家信任的协作过滤推荐算法。该算法分析了用户的不同特征,比较了用户与专家的相似度,通过计算用户-专家相似度矩阵,有效降低了数据集的稀疏性,提高了预测的准确性。在MovieLens数据集上的实验结果表明,改进的算法能够有效缓解冷启动问题,明显提高了系统的推荐精度。
| [1] SHAFER,SEN S W,FRANKOWSKI,et al.Collaborative Filtering Recommender Systems[C]∥International Conference on Intelligent Systems Design & Applications.IEEE,2015:438-443. [2] YANG C,AI C C,JIANG B,et al.Demographic Attribute-based Collaborative Filtering Algorithm[J].Journal of Chinese Computer Systems,2015,36(4):782-786.(in Chinese) 杨超,艾聪聪,蒋斌,等.一种融合人口统计属性的协同过滤算法[J].小型微型计算机系统,2015,36(4):782-786. [3] JANNACH D,ZANKER M,FELFERNIG A,et al.Recommender Systems:An Introduction[M].Int.j.hum.comput.interaction,2010. [4] SUN L F,HUANG M X.Collaborative filtering recommendation algorithm based on user characteristics and item attributes[J].Application Research of Computers,2014,31(2):384-387.(in Chinese) 孙龙菲,黄梦醒.综合用户特征和项目属性的协作过滤推荐算法[J].计算机应用研究,2014,31(2):384-387. [5] SHUO L X,CHAI B F,ZHANG X D.Collaborative filtering algorithm based on improved nearest neighbors[J].Computer Engineering & Applications,2015,51(5):137-141.(in Chinese) 硕良勋,柴变芳,张新东.基于改进最近邻的协同过滤推荐算法[J].计算机工程与应用,2015,51(5):137-141. [6] PENG D W,HU B.A Collaborative Filtering Recommendation Based on User Characteristics and Time Weight[J].Journal of Wuhan University of Technology,2009,31(3):24-28.(in Chinese) 彭德巍,胡斌.一种基于用户特征和时间的协同过滤算法[J].武汉理工大学学报,2009,31(3):24-28. [7] CHOI K,SUH Y.A new similarity function for selecting neighbors for each target item in collaborative filtering[J].Know-ledge-Based Systems,2013,37(1):146-153. [8] AMATRIAIN X,LATHIA N,PUJOL J M,et al.The Wisdom of the Few A Collaborative Filtering Approach Based on Expert Opinions from the Web[C]∥Proceedings of International ACM SIGIR Conference on Research & Development in Information Retrieval.2009:532-539. [9] YUN L,YANG Y,WANG J,et al.Improving rating estimation in recommender using demographic data and expert opinions[C]∥2011 IEEE 2nd International Conference on Software Enginee-ring and Service Science (ICSESS).IEEE,2011:120-123. [10] ΒOζAλ′ Ε,VOZALIS E,MARGARITIS K.Collaborative Filtering enhanced by Demographic Correlation[J].Proceedings of the Aiai Symposium on Professional Practice in Ai Part of World Computer Congress,2004:293-402. [11] LIU J G,ZHOU T,GUO Q,et al.Overview of the Evaluated Algorithms for the Personal Recommendation Systems[J].Complex Systems & Complexity Science,2009,6(3):1-10.(in Chinese) 刘建国,周涛,郭强,等.个性化推荐系统评价方法综述[J].复杂系统与复杂性科学,2009,6(3):1-10. |
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