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» Mining Interval Time Series
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KDD
2006
ACM
172views Data Mining» more  KDD 2006»
14 years 10 months ago
Attack detection in time series for recommender systems
Recent research has identified significant vulnerabilities in recommender systems. Shilling attacks, in which attackers introduce biased ratings in order to influence future recom...
Sheng Zhang, Amit Chakrabarti, James Ford, Fillia ...
KDD
1997
ACM
213views Data Mining» more  KDD 1997»
14 years 1 months ago
A Probabilistic Approach to Fast Pattern Matching in Time Series Databases
Theproblemof efficiently and accurately locating patterns of interest in massivetimeseries data sets is an important and non-trivial problemin a wide variety of applications, incl...
Eamonn J. Keogh, Padhraic Smyth
PKDD
2009
Springer
155views Data Mining» more  PKDD 2009»
14 years 4 months ago
Dynamic Factor Graphs for Time Series Modeling
Abstract. This article presents a method for training Dynamic Factor Graphs (DFG) with continuous latent state variables. A DFG includes factors modeling joint probabilities betwee...
Piotr W. Mirowski, Yann LeCun
SDM
2009
SIAM
164views Data Mining» more  SDM 2009»
14 years 6 months ago
Exact Discovery of Time Series Motifs.
Time series motifs are pairs of individual time series, or subsequences of a longer time series, which are very similar to each other. As with their discrete analogues in computat...
Abdullah Mueen, Eamonn J. Keogh, M. Brandon Westov...
KDD
2010
ACM
199views Data Mining» more  KDD 2010»
14 years 1 months ago
Online discovery and maintenance of time series motifs
The detection of repeated subsequences, time series motifs, is a problem which has been shown to have great utility for several higher-level data mining algorithms, including clas...
Abdullah Mueen, Eamonn J. Keogh