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ICDM
2010
IEEE
216views Data Mining» more  ICDM 2010»
14 years 7 months ago
Data Editing Techniques to Allow the Application of Distance-Based Outlier Detection to Streams
The problem of finding outliers in data has broad applications in areas as diverse as data cleaning, fraud detection, network monitoring, invasive species monitoring, etc. While th...
Vit Niennattrakul, Eamonn J. Keogh, Chotirat Ann R...
CIDM
2007
IEEE
15 years 3 months ago
Incremental Local Outlier Detection for Data Streams
Outlier detection has recently become an important problem in many industrial and financial applications. This problem is further complicated by the fact that in many cases, outlie...
Dragoljub Pokrajac, Aleksandar Lazarevic, Longin J...
ESEM
2007
ACM
14 years 11 months ago
An Approach to Outlier Detection of Software Measurement Data using the K-means Clustering Method
The quality of software measurement data affects the accuracy of project manager’s decision making using estimation or prediction models and the understanding of real project st...
Kyung-A Yoon, Oh-Sung Kwon, Doo-Hwan Bae
VLDB
2005
ACM
153views Database» more  VLDB 2005»
15 years 9 months ago
An effective and efficient algorithm for high-dimensional outlier detection
Abstract. The outlier detection problem has important applications in the field of fraud detection, network robustness analysis, and intrusion detection. Most such applications are...
Charu C. Aggarwal, Philip S. Yu
APBC
2004
121views Bioinformatics» more  APBC 2004»
14 years 11 months ago
Using Emerging Pattern Based Projected Clustering and Gene Expression Data for Cancer Detection
Using gene expression data for cancer detection is one of the famous research topics in bioinformatics. Theoretically, gene expression data is capable to detect all types of early...
Larry T. H. Yu, Fu-Lai Chung, Stephen Chi-fai Chan...