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局部空间离群点算法的改进及其实现 被引量：3

The improvements and experiments of local spatial outlier detecting algorithm
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摘要 LOF算法是一个著名的局部离群点查找方法,该方法赋予了表征每一个空间点偏离程度的数值。但LOF算法存在效率低和性能差的问题,为此对该算法进行了以下两个方面的改进:第一,提出了降低该算法时间复杂度的两步改进方法,并对这两步改进方法的时间复杂度也进行详细分析,第二,使得该算法在查找局部离群点时,不仅考虑了空间属性,也考虑了非空间属性。另外还通过实验测试了LOF算法及其改进方法的时间效率,以及在模拟数据和真实数据情况下的查找离群点的效果。实验结果表明,改进方法具有更好的时间效率和性能。 The LOF （local outlier factor） algorithm is a very distinguished local outlier detecting method,which assigns each object an outlier-degree value, In this paper,we present the two improvements of this algorithm. First, the two step improvements was introduced and their time complexity was analysed. Second,when the algorithm identified local outliers, it can consider spatial attributes and non-spatial attribute. The experiments have tested the executing time of the LOF algorithm and its improvements, the performance of computing synthetic and real data set. The experimental results show that is its improvements outperform the LOF algorithm in efficiency and performance.
作者 胡彩平 秦小麟 任韧
机构地区 南京航空航天大学信息科学与技术学院
出处 《中国图象图形学报》 CSCD 北大核心 2010年第10期1471-1477,共7页 Journal of Image and Graphics
基金 国家高技术研究发展计划(863)项目(NO2007AA01Z404) 国家自然科学基金(60673127) 南京航空航天大学科研启动基金项目(S0848-042) 南京航空航天大学基本科研业务费专项科研项目(NS2010094)
关键词 数据挖掘 空间离群点 可达距离 局部离群因子 data mining spatial outliers teachability distance local outlier factor （LOF）
分类号 TP301.6 [自动化与计算机技术—计算机系统结构] TP18 [自动化与计算机技术—控制理论与控制工程]
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参考文献14

  • 1Han J W Kamber M 范明 孟小峰译.数据挖掘概念与技术[M].北京:机械工业出版杜,2001.147-158.
  • 2Lu W,Han J W. Discovery of general knowledge in large spatial databases [C]// Proceedings of Far East Workshop on Geographic Information Systems. Singapore: World Scientific, 1993 : 275-289.
  • 3Shekhar S,Chawla S.空间数据库[M].谢昆青,马修军,杨冬清,等译.北京:机械工业出版社,2004.
  • 4Hawkins D. Identification of Outliers [ M ]. London: UK: Chapman and Hall, 1980.
  • 5Shekhar S,Lu Changtien,Zhang Pusheng. A unified approach to detecting spatial outliers [J]. Geolnformatica, 2003,7 ( 2 ) : 139- 166.
  • 6Lu Changtien, Chen Dechang,Kou Yufeng. Algorithms for spatial outlier detection [ C ]//Proceedings of the 3rd IEEE International Conference on Data Mining, Melbourne, Florida, USA: IEEE Computer Society,2003 : 597-600.
  • 7Lu Changtien, Chen Dechang, Kou Yufeng. Detecting spatial outliers with multiple attributes [C]//Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence, Sacramento, California, USA : IEEE Computer Society,2003 : 122-128.
  • 8Hu Tianming, Sung S Y. A trimmed mean approach to finding spatial outliers [J]. Intelligent Data Analysis,2004 ( 8 ) : 79-95.
  • 9薛安荣,鞠时光,何伟华,陈伟鹤.局部离群点挖掘算法研究[J].计算机学报,2007,30(8):1455-1463. 被引量：96
  • 10Breunig M,Kriegel H P, Ng R, et al. LOF: Identifying density- based local outliers [ C ]//Proceedings of ACM SIGMOD Conference. New York, USA: ACM, Press 2000: 93-104.

二级参考文献13

  • 1Han Jia-Wei,Kamber Micheline Data Mining:Concepts and Techniques (2nd Edition).San Francisco:Morgan Kaufmann Publishers,2006
  • 2Hawkins D.Identification of Outliers.London:Chapman and Hall,1980
  • 3Knorr E,Ng R.Algorithms for mining distance-based outliers in large datasets//Proceedings of the 24th VLDB Conference.New York,1998:392-403
  • 4Breunig M M,Kriegel H P,Ng R T et al.OPTICS-OF:Identifying local outliers//Proceedings of the 3rd European Conference on Principles and Practice of Knowledge Discovery in Databases.Prague,1999:262-270
  • 5Breunig M,Knegel H P,Ng R et al.LOF:Identifying density-based local outliers//Proceedings of ACM SIGMOD Conference.Dallas,Texas,2000:93-104
  • 6Tang J,Chen Z,Fu A et al.Enhancing effectiveness of outlier detections for low-density patterns//Proceeding of Advances in Knowledge Discovery and Data Mining 6th PacificAsia Conference.Taipei,China,2002:535-548
  • 7Papadimitirou S,Kitagawa H,Gibbons PB,Faloutsos C.LOCI:Fast outlier detection using the local correlation integral//Proceedings of the 19th International Conference on Data Engineering.Bangalore,2003.Los Alamitos:IEEE Computer Society,2003:315-326
  • 8Chawla Sanjay,Sun Pei.SLOM:A new measure for local spatial outliers.Knowledge and Information Systems,2006,9(4):412-429
  • 9Shekhar S,Chawla S.A Tour of Spaual Databases.Upper Saddle River,N.J.:Prentice Hall,2003
  • 10Lu Chang-Tien,Chen De-Chang,Kou Yu-Feng.Detecting spatial outliers with multiple attributes//Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'03).Sacramento,2003:122-128

共引文献216

同被引文献19

引证文献3

二级引证文献11

中国图象图形学报
2010年 第10期

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