[1] 张剑峰,夏云庆,姚建民.微博文本处理研究综述[J].中文信息学报,2012,26(4):21-27. (ZHANG J F, XIA Y Q, YAO J M. A review towards microtext prossing[J]. Journal of Chinese Information Processing, 2012, 26(4): 21-27.) [2] 王连喜.微博短文本预处理及学习研究综述[J].图书情报工作,2013,57(11):125-131. (WANG L X. A literature review on pre-processing and learning of microtext[J]. Library and Information Service, 2013, 57(11): 125-131.) [3] 童薇,陈威,孟小峰. EDM:高效的微博事件检测算法[J].计算机科学与探索,2012(12):1076-1086. (TONG W, CHEN W, MENG X F. EDM: an efficient algorithm for event detection in microblogs[J]. Journal of Frontiers of Computer Science and Technology, 2012(12): 1076-1086.) [4] PHUVIPADAWAT S, MURATA T. Breaking news detection and tracking in Twitter[C]//WI-IAT '10: Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. Washington, DC: IEEE Computer Society, 2010, 3: 120-123. [5] 彭泽映,俞晓明,许洪.大规模短文本的不完全聚类[J].中文信息学报,2011,25(1):54-59. (PENG Z Y, YU X M, XU H. Incomplete clustering for large scale short texts[J]. Journal of Chinese Information Processing, 2011, 25(1): 54-59.) [6] XU T, OARD D W. Wikipedia-based topic clustering for microblogs[J]. Proceedings of the American Society for Information Science & Technology, 2011, 48(1): 1-10. [7] SALTON G, BUCKLEY C. Term-weighting approaches in automatic text retrieval[J]. Information Processing & Management, 1988, 24(5): 513-523. [8] 宗成庆. 统计自然语言处理[M].北京:清华大学出版社,2008:346-349. (ZONG C Q. Statistical natural language processing[M]. Beijing: Tsinghua University Press, 2008: 346-349.) [9] 成卫青,卢艳红.一种基于最大最小距离和SSE的自适应聚类算法[J].南京邮电大学学报(自然科学版), 2015,35(2):102-107. (CHENG W Q, LU Y H. An adaptive clustering algorithm based on maximum and minimum distances and the SSE[J]. Journal of Nanjing University of Posts and Telecommunications (Natural Science Edition), 2015, 35(2): 102-107.) [10] 卢艳红.文本聚类及其在话题检测中的应用研究[D].南京:南京邮电大学,2015:33-34. (LU Y H. Research on text clustering and its application in topic detection analysis [D]. Nanjing: Nanjing University of Posts and Telecommunications, 2015: 33-34.) [11] 熊小兵,周刚,黄永忠,等.新浪微博话题流行度预测技术研究[J].信息工程大学学报,2012,13(4):496-502. (XIONG X B, ZHOU G, HUANG Y Z, et al. Predicting popularity of tweets on Sina Weibo[J]. Journal of Information Engineering University, 2012, 13(4): 496-502.) [12] 63641个用户的新浪微博数据集[EB/OL].[2014-09-24].http://www. datatang.com/data/46758. (63641 users of Sina Weibo data set [EB/OL]. [2014-09-24]. http://www. datatang.com/data/46758.) [13] LIN P Y, LIN Z J, KUANG B Q, et al. A short Chinese text incremental clustering algorithm based on weighted semantics and Naive Bayes[J]. Journal of Computational Information Systems, 2012, 8(10): 4257-4268. [14] 原福永,冯静,符茜茜.微博用户的影响力指数模型[J].现代图书情报技术,2012(6):60-64. (YUAN F Y, FENG J, FU Q Q. Influence index model of micro-blog user[J]. New Technology of Library and Information Service, 2012(6): 60-64.) |