[1] 李子臣. 搜索技术的现状及发展前景[J]. 情报科学, 2007, 25(7): 1114-1120.(Li Zichen. The Present Situation and the Development Foreground of Seeking Technique [J]. Information Science, 2007, 25(7): 1114-1120.)

[2] Vise D A, Malseed M. The Google Story [M]. New York: Delacorte Press, 2005.

[3] Brin S, Page L. The Anatomy of a Large-scale Hypertextual Web Search Engine [J]. Computer Networks and ISDN Systems, 1998, 30 (1-7): 107-117.

[4] Page L, Brin S, Motwani R, et al. The PageRank Citation Ranking: Bringing Order to the Web [EB/OL]. [2013-08-08]. http://ilpubs.stanford.edu:8090/422.

[5] 张立彬, 杨军花, 杨琴茹. 第三代搜索引擎的研究现状及其发展趋向探析[J]. 情报理论与实践, 2008, 31(5): 785-789.(Zhang Libin, Yang Junhua, Yang Qinru. Probe into the Research Status and Developing Trend of the Third Generation Search Engines [J]. Information Studies: Theory and Application, 2008, 31(5): 785-789.)

[6] 傅欣. 第三代搜索引擎的智能化趋势研究[J]. 现代图书情报技术, 2002(6): 28-30. (Fu Xin. Studies on Intelligent Trends in Third Generation Search Engines [J]. New Technology of Library and Information Service, 2002(6): 28-30.)

[7] 陈林, 杨丹, 赵俊芹. 基于语义理解的智能搜索引擎研究[J]. 计算机科学, 2008, 35(6): 152-154. (Chen Lin, Yang Dan, Zhao Junqin. Research on Intelligent Search Engine Based on Semantic Comprehension [J]. Computer Science, 2008, 35(6): 152-154.)

[8] 杨艺, 周元. 基于用户查询意图识别的Web搜索优化模型[J]. 计算机科学, 2012, 39(1): 264-267. (Yang Yi, Zhou Yuan. Web Retrieval Optimization Model Based on User's Query Intention Identification [J]. Computer Science, 2012, 39(1): 264-267.)

[9] Jansen B J, Booth D L, Spink A. Determining the User Intent of Web Search Engine Queries [C]. In: Proceedings of the 16th International Conference on World Wide Web. New York: ACM, 2007: 1149-1150.

[10] 林国, 李伟超. 个性化搜索引擎中用户兴趣模型研究[J]. 软件导刊, 2012, 11(8): 26-28. (Lin Guo, Li Weichao. Research on User Profile in Personalized Search Engine [J]. Software Guide, 2012, 11(8): 26-28.)

[11] MacKay D. Information Theory, Inference, and Learning Algorithms [M]. UK: Cambridge University Press, 2003: 284-292.

[12] Rice J A. Mathematical Statistics and Data Analysis [M]. The 3rd Edition.Belmont: Thomson Brooks/Cole, 2006.

[13] Goldwater S, Griffiths T L, Johnson M. A Bayesian Framework for Word Segmentation: Exploring the Effects of Context [J]. Cognition, 2009, 112(1): 21-54.

[14] Zhang T, Ramakrishnan R, Livny M. BIRCH: An Efficient Data Clustering Method for Very Large Databases [J]. ACM SIGMOD Record, 1996, 25(2): 103-114.

[15] 陈宝林. 最优化理论与算法 [M].第2版.北京: 清华大学出版社, 2005. (Chen Baolin. Optimization Theory and Algo- rithms [M]. The 2nd Edition.Beijing: Tsinghua University Press, 2005.)

[16] 黄名选, 陈燕红. 关联规则挖掘技术研究 [J]. 情报杂志, 2008,27(4): 119-121,115. (Huang Mingxuan, Chen Yanhong. Studies on Association Rules Mining Techniques[J].Journal of Intelligence, 2008,27(4):119-121,115.)

[17] Wu H, Luk R W P, Wong K F, et al. Interpreting TF-IDF Term Weights as Making Relevance Decisions [J]. ACM Transactions on Information Systems (TOIS), 2008, 26(3): Article No.13.

[18] Tan P, Steinbach M, Kumar V. Introduction to Data Mining [M]. Boston: Pearson Addison-Wesley, 2005.

[19] Herlocker J L, Konstan J A, Terveen L G, et al. Evaluating Collaborative Filtering Recommender Systems[J].ACM Transactions on Information Systems (TOIS), 2004, 22(1): 5-53.

[20] Blei D M, Ng A Y, Jordan M I. Latent Dirichlet Allocation [J]. The Journal of Machine Learning Research, 2003,3: 993-1022.

[21] Wikipedia. Jaccard Index [EB/OL]. [2013-10-08]. http://en. wikipedia.org/wiki/Jaccard_index.