[1] 孟小峰, 李勇, 祝建华.社会计算:大数据时代的机遇与挑战[J]. 计算机研究与发展, 2013, 50(12):2483-2491.(MENG X F, LI Y, ZHU J H. Social computing in the era of big data: opportunities and challenges[J]. Journal of Computer Research and Development, 2013, 50(12): 2483-2491.) [2] HOSIO S, GONCALVES J, KOSTAKOS V, et al. Crowdsourcing public opinion using urban pervasive technologies: lessons from real-life experiments in Oulu[J]. Policy & Internet, 2015, 7(2): 203-222. [3] DOUGLAS V A, AULTMAN BECKER A. Encouraging better graphic design in libraries: a creative commons crowdsourcing approach[J]. Journal of Library Administration, 2015, 55(6): 459-472. [4] 张晓航, 李国良, 冯建华.大数据群体计算中用户主题感知的任务分配[J]. 计算机研究与发展, 2015, 52(2):309-317.(ZHANG X H, LI G L, FENG J H. Theme-aware task assignment in crowd computing on big data [J]. Journal of Computer Research and Development, 2015, 52(2): 309-317.) [5] 张引, 陈敏, 廖小飞. 大数据应用的现状与展望[J]. 计算机研究与发展, 2013, 50(增刊2):216-233.(ZHANG Y, CHEN M, LIAO X F. Big data applications: a survey [J]. Journal of Computer Research and Development, 2013, 50(S2):216-233.) [6] 孟韬, 张媛, 董大海.基于威客模式的众包参与行为影响因素研究[J]. 中国软科学, 2014(12):112-123.(MENG T, ZHANG Y, DONG D H. The research on influencing factors of crowdsourcing participating behavior based on wickey model[J]. China Soft Science, 2014(12):112-123.) [7] 叶晨, 王宏志, 周小田, 等. 基于众包的电子商务数据实体分类系统[J]. 计算机研究与发展, 2013, 50(增刊1):405-409.(YE C, WANG H Z, ZHOU X T, et al. Codesourcing-based e-commerce entity classification system[J]. Journal of Computer Research and Development, 2013, 50(S1):405-409.) [8] 叶伟巍, 朱凌.面向创新的网络众包模式特征及实现路径研究[J]. 科学学研究, 2012(1):145-151.(YE W W, ZHU L. Study on the characteristics and achieving pathes for crowdsourcing innovation [J]. Studies in Science of Science, 2012(1):145-151.) [9] 冯剑红, 李国良, 冯建华. 众包技术研究综述[J]. 计算机学报, 2015, 38(9):1713-1726.(FEND J H, LI G L, FEND J H. A survey on crowdsourcing[J]. Chinese Journal of Computers, 2015, 38(9):1713-1726.) [10] 王飞跃, 王晓, 袁勇, 等.社会计算与计算社会:智慧社会的基础与必然[J]. 科学通报, 2015,60(增刊1):460-469.(WANG F Y, WANG X, YUAN Y, et al. Social computing and computational societies: the foundation and consequence of smart societies [J]. Science China Press, 2015,60(S1):460-469.) [11] 刘云浩.群智感知计算[J]. 中国计算机学会通讯, 2012, 8(10):38-41.(LIU Y H. Crowd sensing computing [J]. Communications of the China Computer Federation, 2012, 8(10):38-41.) [12] 赵妍妍, 秦兵, 刘挺.文本情感分析[J]. 软件学报, 2010, 21(8):1834-1848.(ZHAO Y Y, QIN B, LIU T. Sentiment analysis [J]. Journal of Software, 2010, 21(8):1834-1848.) [13] 岳德君, 于戈, 申德荣, 等.基于投票一致性的众包质量评估策略[J]. 东北大学学报(自然科学版), 2014, 35(8): 1097-1101.(YUE D J, YU G, SHEN D R, et al. Crowdsourcing quality evaluation strategies based consistency on voting [J]. Journal of Northeastern University (Natural Science), 2014, 35(8): 1097-1101.) [14] 韩清池, 赵国杰. 基于众包的开放式创新研究:现状与发展方向[J]. 科技进步与对策, 2014, 31(21): 11-16.(HAN Q C, ZHAO G J. Research on the open innovation based on crowdsourcing: state of the art and future directions[J]. Science & Technology Progress and Policy, 2014, 31(21): 11-16.) [15] 朱小宁.支持任务推送的众包系统的研究与实现[D]. 北京:北京邮电大学, 2015:24-95.(ZHU X N. Research and implementation of a crowdsourcing system supporting task routing [D]. Beijing: Beijing University of Posts and Telecommunications, 2015:24-95.) [16] 张志强, 逄居升, 谢晓芹, 等. 众包质量控制策略及评估算法研究[J]. 计算机学报, 2013, 36(8): 1636-1649.(ZHANG Z Q, PANG J S, XIE X Q, et al. Research on crowdsourcing quality control strategies and evaluation algorithm [J]. Chinese Journal of Computers, 2013, 36(8): 1636-1649.) [17] 李勇军, 郭基凤, 缑西梅. 软件"众包"任务分配方法[J]. 计算机系统应用, 2015, 24(2): 1-6.(LI Y J, GUO J F, GOU X M. Software task allocation method in crowdsourcing[J]. Computer Systems & Applications, 2015, 24(2): 1-6.) [18] 潘尔顺, 金垚, 叶亮. 基于逻辑回归的计数型质量特性健壮参数谨慎控制策略[J]. 上海交通大学学报(自然科学版), 2010,44(12):1711-1715.(PAN E S, JIN Y, YE L. Robust parameter control approach with cautious control strategy for attributes quality characteristics based on logistic regression model [J]. Journal of Shanghai Jiaotong University, 2010,44(12):1711-1715.) [19] 毛林, 陆全华, 程涛. 基于高维数据的集成逻辑回归分类算法的研究与应用[J]. 科技通报, 2013,29(12):64-66.(MAO L, LU Q H, CHENG T. The research and application of ensemble logistic regression classification algorithm based on high dimensional data [J]. Bulletin of Science and Technology, 2013,29(12):64-66.) [20] 孙爱程. 基于熵距离的离群点检测及其应用[J]. 无线电工程, 2012,42(6):45-47, 51.(SUN A C. Entropy distance-based outlier detection and its application [J]. Radio Engineering, 2012,42(6):45-47, 51.). [21] LICHMAN, M. UCI machine learning repository [D]. Irvine, CA: University of California, School of Information and Computer Science, 2013. [22] ASUNCION A, WELLING M, SMYTH P, et al. On smoothing and inference for topic models[C]//Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence. Quebec: AUAI Press, 2009: 27-34. |