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查询推荐技术综述 被引量：1

Overviews on Recommender Systems
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摘要 本文介绍了用户搜索中查询推荐技术的相关概念、研究现状;深入分析了目前常见的推荐算法及推荐系统中的隐私保护问题;最后,归纳了查询推荐技术的研究热点。 The concept and principles are presented.And then the active topics,the algorithms and the privacy preserving in recommender systems,were studied.Finally,we pointed out the significantly promising tendency on Recommender systems.
作者 徐勇 沈小玲 赵俊杰
机构地区 安徽财经大学信息工程学院
出处 《微计算机信息》 2011年第5期15-16,14,共3页 Control & Automation
基金 基金申请人:徐勇 项目名称:科技文献推荐系统若干问题研究 基金颁发部门:国家教育部(09YJC870001) 基金申请人:沈小玲 项目名称:基于链接分析的网络科技论文学术影响评价研究 基金颁发部门:国家社会科学基金(09BTQ019) 基金申请人:赵俊杰 项目名称:文本挖掘技术在论文抄袭判定中的应用研究 基金颁发部门:国家教育部(07JC870006)
关键词 推荐系统 协同过滤 数据挖掘 Recommender systems Collaborative filtering Data mining
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献9

  • 1A. M. Rashid. Mining Influence in Recommender Systems. [Ph. D. Thesis], Minneapolis, Minnesota: University of Minnesota,2007.
  • 2E. Rich. User Modeling via Stereotypes. Cognitive Science, 1979, 3(4):329-354.
  • 3D. Goldberg, D. Nichols, B. M. Oki et al. Using Collaborative Filtering to Weave an Information Tapestry. Communications of the ACM, I992, 35(12):61-70.
  • 4W. Hill, L. Stead, M. Rosenstein, et al. Recommending and E- valuating Choices in a Virtual Community of Use. In: proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI95), Denver, Colorado, USA, ACM Press, 1995, 175- 186.
  • 5U. Shardanand, P. Maes. Social Information Filtering: Algorithms for Automating 'wOrd of Mouth'. In: Proceedings of ACM CHI' 95 Conference on Human Factors in Computing Systems, Denver, USA, ACM Press, 1995, 210-217.
  • 6N. Belkin, B. W. Croft. Information Filtering and Information Retrieval: Two Sides of the Same Coin Communication of the ACM, 1992, 35(12): 29-38.
  • 7J. B. Schafer, J. A. Konstan, J. Riedl. E-Commerce Recommen- dation applications. Data Mining and Knowledge Discovery, 2001,5 (1):115-153.
  • 8B. P. S. Murthi, Sumit Sarkar. The Role of the Management Sci- ences in Research on Personalization. MANAGEMENT SCIENCE, Vol. 49, No. 10, October 2003, pp. 1344-1362.
  • 9马琳,苏一丹,莫锦萍.协同推荐系统检测模型的一种优化方法[J].微计算机信息,2010,26(3):207-208. 被引量：1

二级参考文献8

  • 1欧立奇,陈莉,马煜.协同过滤算法中新项目推荐方法的研究[J].微计算机信息,2005,21(11X):186-187. 被引量：10
  • 2P. Chirita, W. Nejdl, and C. Zamfir. Preventing shilling attacks in online recommender systems. In WIDM '05: Proc'. Of the 7th annual ACM Int'l workshop on Web information and data management, pages 67 - 74, New York, NY, 2005. ACM Press.
  • 3LAM S K,RIEDL J.Shilling recommender systems for fun and profit. [C]//Proc of the 13th International Conference on World Wide Web.New York:ACM Press.2004:393-402.
  • 4Mobasher B,Burke R,Bhaumi k R,et al.Effective attack models for shilling item-based collaborative filtering systems In:Proceedings of the 2005 WebKDD,workshop,held in conjunction with ACM SIGKDD 2005,Chicago,Illinois,2005.
  • 5Burke R,Mobasher B,Bhaumik R.Limited knowledge shilling attacks in collaborative filtering systems. In:Proceeding s of the 3rd UCAI Workshop in Intelligent Techniques for Personalization,Edinburgh, Scotland,2005.
  • 60' Mahony M ,Hurley N,Kushrnerick N,et al.Collaborative recommendation:A robustness analysis.ACM Transactions on Intemet Technology,2004,4(4):344- 377.
  • 7R. Burke, B. Mobasher, C. Williams, and R. Bhaumik. Classification features for attack detection in collaborative recommender systems. In To appear in Proceedings of The Twelfth ACM SIGKDD International Conference on Knowledge Discovery and- Data Mining (KDD 2006), Philadelphia, PA, August 2006.
  • 8Mobasher, B., Burke, R., Bhaumik, R., Williams, C.: Towards trustworthy recommender systems: An analysis of attack models and algorithm robustness. ACM Transactions on Internet Technology 7(4) (2007).

同被引文献9

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微计算机信息
2011年 第5期

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