On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms

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On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms

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International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining table of contents

Boston, Massachusetts, United States

Pages: 320 - 324

Year of Publication: 2000

ISBN:1-58113-233-6

Authors

Kenji Yamanishi	NEC Corporation, 4-1-1, Miyazaki, Miyamae, Kawasaki, Kanagawa, 216-8555, Japan
Jun-Ichi Takeuchi	NEC Corporation, 4-1-1, Miyazaki, Miyamae, Kawasaki, Kanagawa, 216-8555, Japan
Graham Williams	CSIRO Mathematical and Information Sciences, GPO Box 664, Canberra ACT, 2601 Australia
Peter Milne	CSIRO Mathematical and Information Sciences, GPO Box 664, Canberra ACT 2601, Australia

Sponsors

SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
AAAI : Am Assoc for Artifical Intelligence
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 13, Downloads (12 Months): 64, Citation Count: 23

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY 23

	Tsuyoshi IDÉ , Hisashi KASHIMA, Eigenspace-based anomaly detection in computer systems, Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, August 22-25, 2004, Seattle, WA, USA
	Kenji Yamanishi , Jun-ichi Takeuchi, Discovering outlier filtering rules from unlabeled data: combining a supervised learner with an unsupervised learner, Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, p.389-394, August 26-29, 2001, San Francisco, California
	Kenji Yamanishi , Jun-ichi Takeuchi, A unifying framework for detecting outliers and change points from non-stationary time series data, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, July 23-26, 2002, Edmonton, Alberta, Canada
	M. I. Petrovskiy, Outlier Detection Algorithms in Data Mining Systems, Programming and Computing Software, v.29 n.4, p.228-237, July-August 2003
	Markos Markou , Sameer Singh, Novelty detection: a review—part 1: statistical approaches, Signal Processing, v.83 n.12, p.2481-2497, December 2003
	Stefano Zanero , Sergio M. Savaresi, Unsupervised learning techniques for an intrusion detection system, Proceedings of the 2004 ACM symposium on Applied computing, March 14-17, 2004, Nicosia, Cyprus
	Zengyou He , Xiaofei Xu , Shengchun Deng, Discovering cluster-based local outliers, Pattern Recognition Letters, v.24 n.9-10, p.1641-1650, 01 June 2003
	Satoshi Morinaga , Kenji Yamanishi, Tracking dynamics of topic trends using a finite mixture model, Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, August 22-25, 2004, Seattle, WA, USA
	Hang Li , Kenji Yamanishi, Topic analysis using a finite mixture model, Information Processing and Management: an International Journal, v.39 n.4, p.521-541, July 2003
	Kenji Yamanishi , Yuko Maruyama, Dynamic syslog mining for network failure monitoring, Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, August 21-24, 2005, Chicago, Illinois, USA
	Fabrizio Angiulli , Clara Pizzuti, Outlier Mining in Large High-Dimensional Data Sets, IEEE Transactions on Knowledge and Data Engineering, v.17 n.2, p.203-215, February 2005
	Haifeng Chen , Guofei Jiang , Cristian Ungureanu , Kenji Yoshihira, Failure detection and localization in component based systems by online tracking, Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, August 21-24, 2005, Chicago, Illinois, USA
	Mohammad Saniee Abadeh , Jafar Habibi , Zeynab Barzegar , Muna Sergi, A parallel genetic local search algorithm for intrusion detection in computer networks, Engineering Applications of Artificial Intelligence, v.20 n.8, p.1058-1069, December, 2007
	Haifeng Chen , Guofei Jiang , Cristian Ungureanu , Kenji Yoshihira, Combining supervised and unsupervised monitoring for fault detection in distributed computing systems, Proceedings of the 2006 ACM symposium on Applied computing, April 23-27, 2006, Dijon, France
	M. Saniee Abadeh , J. Habibi , C. Lucas, Intrusion detection using a fuzzy genetics-based learning algorithm, Journal of Network and Computer Applications, v.30 n.1, p.414-428, January 2007
	Fabrizio Angiulli , Fabio Fassetti, Detecting distance-based outliers in streams of data, Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, November 06-10, 2007, Lisbon, Portugal
	Taghi M. Khoshgoftaar , Naeem Seliya , Kehan Gao, Detecting noisy instances with the rule-based classification model, Intelligent Data Analysis, v.9 n.4, p.347-364, July 2005
	Kenji Yamanishi , Jun-Ichi Takeuchi , Graham Williams , Peter Milne, On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms, Data Mining and Knowledge Discovery, v.8 n.3, p.275-300, May 2004
	Haifeng Chen , Guofei Jiang , Kenji Yoshihira, Monitoring High-Dimensional Data for Failure Detection and Localization in Large-Scale Computing Systems, IEEE Transactions on Knowledge and Data Engineering, v.20 n.1, p.13-25, January 2008
	ShengYi Jiang , Xiaoyu Song , Hui Wang , Jian-Jun Han , Qing-Hua Li, A clustering-based method for unsupervised intrusion detections, Pattern Recognition Letters, v.27 n.7, p.802-810, May 2006
	Haifeng Chen , Guofei Jiang , Kenji Yoshihira, Failure Detection in Large-Scale Internet Services by Principal Subspace Mapping, IEEE Transactions on Knowledge and Data Engineering, v.19 n.10, p.1308-1320, October 2007
	Hans-Peter Kriegel , Matthias S hubert , Arthur Zimek, Angle-based outlier detection in high-dimensional data, Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, August 24-27, 2008, Las Vegas, Nevada, USA
	Faizah Shaari , Azuraliza Abu Bakar , Abdul Razak Hamdan, Outlier detection based on rough sets theory, Intelligent Data Analysis, v.13 n.2, p.191-206, April 2009