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» Mining Dense Periodic Patterns in Time Series Data
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WSDM
2012
ACM
245views Data Mining» more  WSDM 2012»
12 years 2 months ago
The early bird gets the buzz: detecting anomalies and emerging trends in information networks
In this work we propose a novel approach to anomaly detection in streaming communication data. We first build a stochastic model for the system based on temporal communication pa...
Brian Thompson
KDD
2010
ACM
218views Data Mining» more  KDD 2010»
13 years 11 months ago
Online multiscale dynamic topic models
We propose an online topic model for sequentially analyzing the time evolution of topics in document collections. Topics naturally evolve with multiple timescales. For example, so...
Tomoharu Iwata, Takeshi Yamada, Yasushi Sakurai, N...
ICST
2009
IEEE
14 years 1 months ago
Seasonal Variation in the Vulnerability Discovery Process
Vulnerability discovery rates need to be taken into account for evaluating security risks. Accurate projection of these rates is required to estimate the effort needed to develop ...
HyunChul Joh, Yashwant K. Malaiya
KDD
2005
ACM
119views Data Mining» more  KDD 2005»
14 years 18 days ago
LIPED: HMM-based life profiles for adaptive event detection
In this paper, the proposed LIPED (LIfe Profile based Event Detection) employs the concept of life profiles to predict the activeness of event for effective event detection. A gro...
Chien Chin Chen, Meng Chang Chen, Ming-Syan Chen
PKDD
2005
Springer
159views Data Mining» more  PKDD 2005»
14 years 18 days ago
Fast Burst Correlation of Financial Data
We examine the problem of monitoring and identification of correlated burst patterns in multi-stream time series databases. Our methodology is comprised of two steps: a burst dete...
Michail Vlachos, Kun-Lung Wu, Shyh-Kwei Chen, Phil...