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» Mining Complex Time-Series Data by Learning Markovian Models
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KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 4 days ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
KDD
2009
ACM
181views Data Mining» more  KDD 2009»
14 years 2 months ago
An exploration of climate data using complex networks
To discover patterns in historical data, climate scientists have applied various clustering methods with the goal of identifying regions that share some common climatological beha...
Karsten Steinhaeuser, Nitesh V. Chawla, Auroop R. ...
WINE
2005
Springer
268views Economy» more  WINE 2005»
14 years 1 months ago
Mining Stock Market Tendency Using GA-Based Support Vector Machines
In this study, a hybrid intelligent data mining methodology, genetic algorithm based support vector machine (GASVM) model, is proposed to explore stock market tendency. In this hyb...
Lean Yu, Shouyang Wang, Kin Keung Lai
KDD
2008
ACM
121views Data Mining» more  KDD 2008»
14 years 8 months ago
Reconstructing chemical reaction networks: data mining meets system identification
We present an approach to reconstructing chemical reaction networks from time series measurements of the concentrations of the molecules involved. Our solution strategy combines t...
Yong Ju Cho, Naren Ramakrishnan, Yang Cao
KDD
2004
ACM
198views Data Mining» more  KDD 2004»
14 years 28 days ago
Mining traffic data from probe-car system for travel time prediction
We are developing a technique to predict travel time of a vehicle for an objective road section, based on real time traffic data collected through a probe-car system. In the area ...
Takayuki Nakata, Jun-ichi Takeuchi