A New Outlier Mining Method Based on CLIQUE in Multi-Database

Abstract:

As a branch of Data-Mining, outlier mining is a promising prospect, and clustering analyse is a kind of technology in spatial outlier mining. The paper analyse the clustering arithmetic , compare some arithmetic of Clustring, and discuss the strongpoint and shortpoint of them.The paper research the spatial data and Outlier attributes in high dimensional space. And analysing the CLIQUE algorithm to detect the Outlier in high dimensional space, this approach can find the outliers in high-dimensional space effectively. In conclusion, the main trends of spatial outlier mining are forecaste.

• Periodical: Advanced Materials Research (Volumes 532-533)
• Pages: 959-963
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.532-533.959
• Online since: June 2012
• Authors: Xiang Qin Xiang, Deng Sheng Liu
• Keywords: CLIQUE Algorithm, Clustering Analysis, Data Mining (DM), Outlier

References

[1] Han Jiawei Micheline Kamber. Data Mining: Comcepts and Techniques, second edition, Morgan Kaufmann Publishers Inc., (2001).

[2] Aggarawal C C, Yu P S. Outliers Detection for High Dimen2 sional Data: In: Aref W G, eds. Proceedings of the ACM SIGMOD International Conference on Management of Data. Santa Barbara, CA: ACM Press, 2001: 37-47.

[3] Tukey J W. Exploratory Data Analysis[M]. MA: Addison2Wesley and Sons, Inc., (1994).

[4] Ester, M., Kriegel, H.P., Sander, J., and Xu, X. 1996. A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining, Portland, Oregon, USA: AAAI Press, p.226.

DOI: 10.1109/icde.1998.655795

[5] Struyf A，Rousseeuw P J. High 2dimensional Computation of the Dee2 pest Location[ J ]. Computational Statistics and Data Analysis, 2000, 34: 415-426.

DOI: 10.1016/s0167-9473(99)00112-7

[6] Knorr EM，NgRT. Algorithms forMiningDistance2based Outliers in Large Datasets[C]. New York: Proc. of Int. Conf. Very Large Data2 bases(VLDB'98), 1998. 392-403.

[7] WangW, Yang J, Muntz T R. Sting: A Statistical Information Grid App roach to SpatialDataMining[A]. JarkeM, CareyM J, Dittrich K R, etal. Proc. of Bases[C]. Athens: Morgan Kaufmann, (1997).

[8] Stan Salvador and Philip Chan, Determining the Number of Clusters/Segments in Hierarchical Clustering/Segmentation Algorithms, Proc. 16th IEEE Intl. Conf. on Tools with AI, p.576–584, (2004).

DOI: 10.1109/ictai.2004.50