User Identifying Algorithm Based on Quantum Computing
ZHU Wan-ning1, LIU Zhi-hao2
1. Institute of Software Engineering, Jinling Institute of Technology, Nanjing, Jiangsu 210000, China;
2. Institute of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu 210096, China
Abstract：This paper presents an IP address finding algorithm based on improved Grover algorithm.At present,Internet is full of massive information.The weblogs contain lots of valuable information that must be analyzed for useful detection like behavior pattern of user.And the user identifying is the previous work.In the past researching of user identifying algorithms,most results focus on the accuracy of identifying user instead of the performance.This paper shows two IP address quick searching algorithms,namely record expansion searching algorithm and record non-expansion searching algorithm based on Grover searching algorithm.The query complexity of the record non-expansion searching algorithm gets quadratic acceleration.
[1] LIN S,JHENG Y,YU C.Combining ranking concept and social network analysis to detect collusive groups in online auctions[J].Expert Systems with Applications,2012,39(10):9079-9086.
[2] DEVI B N,DEVI Y R,RANI B P,RAO R R.Design and implementation of web usage mining intelligent system in the field of e-commerce[J].Procedia Engineering,2012,30:20-27.
[3] FONG A C M,ZHOU B,HUI S,TANG T,HONG G.Generation of personalized ontology based on consumer emotion and behavior analysis[J].IEEE Transactions on Affective Computing,2012,3(2):152-164.
[4] COOLEY Robert,MOBASHER Bamshad,SRIVASTAVA J aideep.Data preparation for mining World Wide Web browsing patterns[J].Knowledge and Information Systems,1999,1(1):5-32.
[5] CHEN Min,MAO Shiwen,LIU Yunhao.Big data:A survey[J].Mobile Networks and Applications,2014,19(2):171-209.
[6] CHOI J,LEE G.New techniques for data preprocessing based on usage logs for efficient web user profiling at client side[A].Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence And Intelligent Agent Technology[C].Washington DC,USA:IEEE Press,2009.3.54-57.
[7] NASRAOUI O,SOLIMAN M,SAKA E,BADIA A,GERMAIN R.A web usage mining framework for mining evolving user profiles in dynamic web sites[J].IEEE Transactions on Knowledge and Data Engineering,2008,20(2):202-215.
[8] MAYER J R,MITCHELL J C.Third-party web tracking:Policy and technology[A].Proceedings of the 2012 IEEE Symposium on Security and Privacy[C].San Francisco,USA:IEEE Press,2012.413-427.
[9] INBARANI H H,THANGAVEL K,PETHALAKSHMI A.Rough set based feature selection for web usage mining[A].Proceedings of the 2007 International Conference on Computational Intelligence and Multimedia Applications[C].Sivakasi,TamilNadu,India,2007,1.33-38.
[10] KOSALA R,BLOCKEEL H.Web mining research:A survey[J].SIGKDD Explorations,2000,2:1-15.
[11] 黄健青,黄浩.Web日志分析中数据预处理的设计与实现[J].河南科技大学学报(自然科学版),2009,30(5):45-48. HUANG Jianqing,HUANG Hao.Design and implementation of data preprocessing in web log analysis[J].Journal of Henan University of Science & Technology (Natural Science),2009,30(5):45-48.(in Chinese)
[12] 侯枫.Web日志数据预处理[J].河南工程学院学报(自然科学版),2008,20(3):54-57. HOU Feng.Web log data preparation[J].Journal of Hennan Institute of Engineering (Natural Science),2008,20(3):54-57.(in Chinese)
[13] 纪良浩,王国胤,杨勇.基于协作过滤的Web日志数据预处理研究[J].重庆邮电学院学报(自然科学版),2006,18(5):646-649. JI Lianghao,WANG Guoying,YANG Yong.Research of web log data preprocessing based on collaborative filtering[J].Journal of ChongQing University of Posts and Telecommunications (Natural Science),2006,18(5):646-649.(in Chinese)
[14] 邹根,闻立杰.基于支持向量机的Web日志用户标志修正算法[J].计算机集成制造系统,2011,17(8):1851-1855. ZHOU Gen,WEN Lijie.User identifier correction algorithm in web logs based on support vector machine[J].Computer Integrated Manufacturing Systems,2011,17(8):1851-1855.(in Chinese)
[15] DICK Stenmark.Identifying clusters of user behavior in intranet search engine log files[J].Journal of the American Society for Information Science and Technology,2008,59(14):2232-2243.
[16] SANTRA A K,JAYASUDHA S.Classification of web log data to identify interested users using naïve bayesian classification[J].International Journal of Computer Science Issues,2012,9:381-384.
[17] GROVER L K.Quantum mechanics helps in searching for a needle in a haystack[J].Physical Review Ltters,1997,79(2):325-328.
[18] ZHU Wanning,CHEN Hanwu,LIU Zhihao,XUE Xilin.Grover algorithm for multi-objective searching with iteration auto-controlling[A].Proceedings of the Fifth International Conference on Swarm Intelligence[C].Hefei,China:ICSI Press,2014,8794.357-364.
[19] BOYER M,BRASSARD G,HФYER P,et al.Tight bounds on quantum searching[J].Fortschritte Der Physik (Progress of Physiks),1998,46(4-5):493-505.
2018, Vol. 46 
