In this paper, we introduce EVE, a generic framework for event detection where events can
also include outliers, model changes and drifts. Various methods for event detection have …

EDF3 hires special contracts with costumers to flatten the consumption peaks. Smart meters
are able to record consumptions and will be set up over 35 millions households. In this …

In recent years, the amount of data to process has increased in many application areas such
as network monitoring, web click and sensor data analysis. Data stream mining answers to …

In France, the currently emerging “smart grid” and more particularly the 35 millions of “smart
meters” will produce a large amount of daily updated metering data. The main french …

There exists a large body of work on online drift detection with the goal of dynamically
finding and maintaining changes in data streams. In this paper, we adopt a query-based …

An interesting challenge in data stream mining is the detection of events where events are
generally defined as anything previously unknown in the data. Therefore outliers, but also …

Variability in Big Data refers to data whose meaning changes continuously. For instance,
data derived from social platforms and from monitoring applications, exhibits great …

In recent years, problems relating to the analysis of data streams have become widespread.
A data stream is a collection of time ordered observations x1, x2,... generated from the …

Equipment diagnosis and condition monitoring techniques employing the vibration method
have been established and are widely used as diagnostic methods for rolling bearings …

L'analyse de flux de données traite des données massives grâce à des algorithmes en ligne
qui évitent le stockage exhaustif des données. La détection de changements dans la …