ELKI is a unied software framework, designed as a tool suitable for evaluation of dierent algorithms on high dimensional realvalued feature-vectors. A special case of high dimens...
Elke Achtert, Thomas Bernecker, Hans-Peter Kriegel...
We have various interesting time series data in our daily life, such as weather data (e.g., temperature and air pressure) and stock prices. Polyline chart is one of the most commo...
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. ...
Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...
Similarity search in time series data is required in many application fields. The most prominent work has focused on similarity search considering either complete time series or si...
A method for approximate subsequence matching is introduced, that significantly improves the efficiency of subsequence matching in large time series data sets under the dynamic ti...
Managing large-scale time series databases has attracted significant attention in the database community recently. Related fundamental problems such as dimensionality reduction, tr...
Title of Dissertation: INTERACTIVE GRAPHICAL QUERYING OF TIME SERIES AND LINEAR SEQUENCE DATA SETS Harry Hochheiser, Doctor of Philosophy, 2003 Dissertation directed by: Professor...
We investigate techniques for visualizing time series data and evaluate their effect in value comparison tasks. We compare line charts with horizon graphs--a space-efficient time ...
Existing techniques to mine periodic patterns in time series data are focused on discovering full-cycle periodic patterns from an entire time series. However, many useful partial ...