A Survey on Anomalies Detection using Density Based - Rank Based Outlier Detection Methods

Authors(2) :-Nehal Patel, Jayna Shah

Outlier Analysis is important research area in data mining. Outlier detection is the process of finding an outlying pattern from a given dataset. Outlier detection became an important subject in different knowledge domains. The aim of this paper is to present various Density and Rank based techniques of outlier detection. So a researcher can get direction with these approaches and they can be integrated with any kind of general Applications.

Authors and Affiliations

Nehal Patel
Computer Engineering, Sardar Vallabhbhai Patel Institute of Technology, Vasad, Gujarat, India
Jayna Shah
Computer Engineering, Sardar Vallabhbhai Patel Institute of Technology, Vasad, Gujarat, India

Outlier Analysis, Anomaly Detection, Density Based, Rank Based.

  1. Breunig, M.M., Kriegel, H.-P., Ng, R.T., Sander, J.,” Lof: identifying density-based local outliers”, ACM Sigmod Record, vol. 29, pp. 93–104. ACM (2000).
  2. Tang, J., Chen, Z., Fu, A.W., Cheung, D.W.,” Enhancing effectiveness of outlier detections for low density patterns”, vol. 2336, pp. 535–548. Springer, Heidelberg (2002).
  3. Jin, W., Tung, A.K.H., Han, J., Wang, W.,” Ranking outliers using symmetric neighborhood relationship”, vol. 3918, pp. 577–593. Springer, Heidelberg (2006).
  4. Huang, H., Mehrotra, K., Mohan, C.K.,”Rank-based outlier detection”, 83(3), pp. 518–531. Journal of Statistical Computation and Simulation (2013).
  5. Huang, Huaming, Kishan Mehrotra, and Chilukuri Mohan.,"Algorithms for detecting outliers via clustering and ranks.", pp. 20-29. Advanced Research in Applied Artificial Intelligence (2012).
  6. R. Baeza-Yates and B. Ribeiro-Neto,“Modern information retrieval”, Addison-Wesley Longman Publishing Co. Inc., Boston (1999).
  7. X. Meng and Z. Chen,“On user-oriented measurements of effectiveness of web information retrieval systems,", pp. 527-533, In Proceeding of the international conference on internet computing (2004).
  8. G. Salton,”Automated text processing: The transformation, analysis, and retrieval of information by computer.”, Addison-Wesley Longman Publishing Co. Inc., Boston (1998).
  9. H. Cao, G. Si, Y. Zhang, and L. Jia, ,”Enhancing effectiveness of density-based outlier mining scheme with density-similarity-neighbor-based outlier factor", Expert Systems with Applications: An International Journal, vol. 37, December (2010).
  10. J. Tang, Z. Chen, A. W. Fu, and D. W. Cheung,“Capabilities of outlier detection schemes in large datasets, framework and methodologies.," Knowledge and Information Systems, vol. 11, no. 1, pp. 45-84,(2006).

Publication Details

Published in : Volume 3 | Issue 2 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 131-137
Manuscript Number : CSEIT1831439
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Nehal Patel, Jayna Shah, "A Survey on Anomalies Detection using Density Based - Rank Based Outlier Detection Methods", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 2, pp.131-137, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT1831439

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