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ESEM
2007
ACM
15 years 1 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
CIDM
2007
IEEE
15 years 6 months ago
Privacy Preserving Burst Detection of Distributed Time Series Data Using Linear Transforms
— In this paper, we consider burst detection within the context of privacy. In our scenario, multiple parties want to detect a burst in aggregated time series data, but none of t...
Lisa Singh, Mehmet Sayal
ICDE
2009
IEEE
125views Database» more  ICDE 2009»
16 years 1 months ago
Temporal Outlier Detection in Vehicle Traffic Data
Outlier detection in vehicle traffic data is a practical problem that has gained traction lately due to an increasing capability to track moving vehicles in city roads. In contrast...
Xiaolei Li, Zhenhui Li, Jiawei Han, Jae-Gil Lee
IPOM
2009
Springer
15 years 6 months ago
A Labeled Data Set for Flow-Based Intrusion Detection
Abstract. Flow-based intrusion detection has recently become a promising security mechanism in high speed networks (1-10 Gbps). Despite the richness in contributions in this field...
Anna Sperotto, Ramin Sadre, Frank van Vliet, Aiko ...
ASIAN
2005
Springer
130views Algorithms» more  ASIAN 2005»
15 years 1 months ago
A Hybrid Method for Detecting Data Stream Changes with Complex Semantics in Intensive Care Unit
Abstract. Detecting changes in data streams is very important for many applications. This paper presents a hybrid method for detecting data stream changes in intensive care unit. I...
Ting Yin, Hongyan Li, Zijing Hu, Yu Fan, Jianlong ...