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» Do we need experts for time series forecasting
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SDM
2010
SIAM
156views Data Mining» more  SDM 2010»
13 years 7 months ago
Unsupervised Discovery of Abnormal Activity Occurrences in Multi-dimensional Time Series, with Applications in Wearable Systems
We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
Alireza Vahdatpour, Majid Sarrafzadeh
SSDBM
2005
IEEE
175views Database» more  SSDBM 2005»
13 years 11 months ago
Assumption-Free Anomaly Detection in Time Series
Recent advancements in sensor technology have made it possible to collect enormous amounts of data in real time. However, because of the sheer volume of data most of it will never...
Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamon...
BMCBI
2006
169views more  BMCBI 2006»
13 years 5 months ago
Machine learning techniques in disease forecasting: a case study on rice blast prediction
Background: Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their ...
Rakesh Kaundal, Amar S. Kapoor, Gajendra P. S. Rag...
KDD
2012
ACM
221views Data Mining» more  KDD 2012»
11 years 8 months ago
Fast mining and forecasting of complex time-stamped events
Given huge collections of time-evolving events such as web-click logs, which consist of multiple attributes (e.g., URL, userID, timestamp), how do we find patterns and trends? Ho...
Yasuko Matsubara, Yasushi Sakurai, Christos Falout...
SMA
2009
ACM
223views Solid Modeling» more  SMA 2009»
14 years 10 days ago
Particle-based forecast mechanism for continuous collision detection in deformable environments
Collision detection in geometrically complex scenes is crucial in physical simulations and real time applications. Works based on spatial hierarchical structures have been propose...
Thomas Jund, David Cazier, Jean-François Du...