期刊文献+

一种优化的推荐算法 被引量:1

An improved recommendation algorithm
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摘要 对个性化推荐系统算法进行改进,首先,不仅考虑用户所选的商品,而且考虑用户的打分,从而将资源分配法扩展为含权资源分配;其次,考虑用户的固有相似性.把这两方面相结合,发展了新的算法.数值试验表明,改进后的方法显著提高了推荐的精度和个性化程度. This paper presents an improved algorithm for personal recommendation. It takes not only the merchandise selected by users into account, but also the ratings given by the users. Then, it considers the inherent similarities between the users. Combining these two factors together, a new algorithm is developed. The numerical simulation results show that the presented algorithm can obviously enhance the accuracy and personality of the recommendation.
出处 《扬州大学学报(自然科学版)》 CAS CSCD 北大核心 2009年第4期18-21,共4页 Journal of Yangzhou University:Natural Science Edition
基金 国家自然科学基金重点资助项目(10635040) 面上资助项目(70671089)
关键词 个性化推荐 资源分配 固有相似性 recommendation system resource allocation occupation similarity
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参考文献9

  • 1汪秉宏,周涛,王文旭,杨会杰,刘建国,赵明,殷传洋,韩筱璞,谢彦波.当前复杂系统研究的几个方向[J].复杂系统与复杂性科学,2008,5(4):21-28. 被引量:33
  • 2刘建国,周涛,汪秉宏.个性化推荐系统的研究进展[J].自然科学进展,2009,19(1):1-15. 被引量:437
  • 3ZHANG Yi-cheng, BLATTNER M, YU Yi-kuo. Heat conduction process on community networks as a recommendation model [J]. Phys Rev Lett, 2007, 99(15): 154301:1-4.
  • 4ZHANG Yi-cheng, MEDO M, REN Jie, et al. Recommendation model based on opinion diffusion [J]. Europhys Lett, 2007, 80(6): 68003:1-5.
  • 5ZHOU Tao, REN Jie, MEDO M, et al. Bipartite network projection and personal recommendation [J]. Phys Rev E, 2007, 76(4): 046115:1-7.
  • 6ZHOU Tao, JIANG Luo-luo, SU Ri-qi, et al. Effect of initial configuration on network-based recommendation [J]. Europhys Lett, 2008, 81(5): 58004:1-6.
  • 7LIU Jian-guo, WANG Bing-hong, GUO Qiang. Improved collaborative filtering algorithm via information transformation [J]. Int J Mod Phys C, 2009, 20(2):285-293.
  • 8JIA Chun-xiao, LIU Run-ran, SUN Duo, et al. A new weighting method in network-based recommendation [J]. Physica A, 2008, 387(23): 5887-5891.
  • 9OU Qing, JIN Ying-di, ZHOU Tao, et al. Power-law strength-degree correlation from resource-allocation dynamics on weighted networks [J]. Phys Rev E, 2007, 75(2): 021102: 1-5.

二级参考文献113

  • 1Resnick P, lakovou N, Sushak M, et al. GroupLens: An open architecture for collaborative filtering of netnews. Proc 1994 Computer Supported Cooperative Work Conf, Chapel Hill, 1994: 175-186
  • 2Hill W, Stead L, Rosenstein M, et al. Recommending and evaluating choices in a virtual community of use. Proc Conf Human Factors in Computing Systems. Denver, 1995:194 -201
  • 3梅田望夫.网络巨变元年-你必须参加的大未来.先觉:先觉出版社,2006
  • 4Adomavicius G, Tuzhilin A. Expert-driven validation of Rule Based User Models in personalization applications. Data Mining and Knowledge Discovery, 2001, 5(1-2):33-58
  • 5Adomavicius G, Tuzhilin A. Toward the next generation of recommender systems: A survey of the state-of-the art and possible extensions. IEEE Trans on Knowledge and Data Engineering, 2005, 17(6): 734-749
  • 6Rich E. User modeling via stereotypes. Cognitive Science, 1979, 3(4) : 329-354
  • 7Goldberg D, Nichols D, Oki BM, et al. Using collaborative filtering to weave an information tapestry. Comm ACM, 1992, 35(12):61-70
  • 8Konstan JA, Miller BN, Maltz D, el al. GroupLens: Applying collaborative filtering to usenet news. Comm ACM, 1997, 40(3) : 77-87
  • 9Shardanand U, Maes P. Social information filtering: Algorithms for automating ‘Word of Mouth'. Proe Conf Human Factors in Computing Systems Denver, 1995: 210-217
  • 10Linden G, Smith B, York J. Amazon. corn recommendations: hem-to-item collaborative filtering. IEEE Internet Computing, 2003, 7(1): 76-80

共引文献467

同被引文献11

  • 1LIU Run-ran, JIA Chun xiao, ZHOU Tao, et al. Personal recommendation via modified collaborative filtering [J]. Phys A: Stat Mech Appl, 2009, 388(4): 462-468.
  • 2RESNICK P, IACOVOU N. SUCHAK M, et al. Grouplens: an open architecture for collaborative filtering of Netnews [C]//Proceedings of ACM 1994 Conference on Computer Supported Cooperative work. New York: ACM, 1994: 175-186.
  • 3BREESE J S, ttECKERMAN D, KADIE C. Empirical analysis of predictive algorithms for collaborative filte- ring [C]//Proc 14th Conf Uncertainty in Artificial Intelligence. San Francisco: Morgan Kaufmann Publishers, 1998: 1-18.
  • 4ZHOU Tao, REN Jie, MEDO M, et al. Bipartite network projection and personal recommendation[J]. Phys RevE, 2007, 76(4): 046115:1-7.
  • 5JIA Chun-xiao, I.IU Run-ran, SUN Duo, et al. A new weighting method in network-based recommendation [J]. Phys A: Star Mech Appl, 2008, 387(23) : 5887-5891.
  • 6LIU Jian-guo, WANG Bing-hong, GUO Qiang. Improved collaborative filtering algorithm via information trans formation [J]. Int J Mod PhysC, 2009, 20(2):285-293.
  • 7ZHOU Tao, JIANG Luo luo, SU Ri-qi, et al. Effect of initial configuration on network-based recommendation [J]. Europhys Lett, 2008, 81(5): 58004:1-6.
  • 8ZHANG Yi cheng, MEDO M, REN Jie, et al. Recommendation model based on opinion diffusion[J]. Euro- phys hett, 2007, 80(6): 68003: 1-5.
  • 9OU Qing, JIN Ying-di, ZHOU Tao, et al. Power law strength degree correlation from resource-allocation dy namics on weighted networks[J]. Phys Rev E, 2007, 75(2): 021102: 1-5.
  • 10汪秉宏,周涛,王文旭,杨会杰,刘建国,赵明,殷传洋,韩筱璞,谢彦波.当前复杂系统研究的几个方向[J].复杂系统与复杂性科学,2008,5(4):21-28. 被引量:33

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