EXPRES is a temporal data mining tool which analyzes longitudinal data (i.e., multivariate time-series) representing the observation over time of attributes descriptive of a dynamic domain (e.g., process or phenomenon). Its functionalities are:
In formal terms, first
(see Figure below)
(see Figure below)
A state Sj is defined in terms of
An evente is defined in terms of
The functional architecture of EXPRES consist of following components:
SEGMENTATION - DETERMINATION OF TEMPORAL STATES- ATRE. MPare split through a multi-variate time-series segmentation which exploits first a first a top-down strategy then a bottom-up one. For each segment a characterization is produced by resorting to ILP ATRE System which return the element Cj.
TRIGGERING EVENTS DISCOVERER - ATRE. For each pair of temporal states, this step first generates candidate events through a Change Mining technique and ATRE system, then selects the sequence of the most statistically ones
EXPLANATORY PATTERN MINER - SPADA. This step mines sequential patterns from the sequences of events discovered in a finite set of scenarios. It exploits the SPADA relational pattern mining system.
TIME SERIES FORECASTING ENSEMBLE - TEMPORAL STATE FORECASTING. This step predicts the possible state following to the last determined state. It exploits an ensemble of neural networks to predicts measurements following MPn} and ATRE system to induce a characterization in form of state of these measurements.
In this scenario, the goal is to acquire knowledge among sleep, disordered breathing and cardiovascular disease, for instance temporal information about cardiovascular and breathing disorders (events) which may determine the change from a physiological stage (state) to another one during sleep. The dataset concerns the polysomnography of only one patient observed from 21.30 p.m. to 6.30 a.m. (Sleep Heart Health Study).
Application: Air Pollution
In this scenario, the goal is to acquire knowledge among pollutant emissions, meteorological conditions and hospitalization, for instance temporal information about events in the form of pollutant emissions, meteorological conditions which may determine critical human health conditions (states). The dataset concerns thirteen US cities and it comes from a study on the mortality, air pollution, and meteorological data in the period 1987-2000 (NMMAPS.)
EXPRES is provided as a java application and runs with a JVM 1.5 or higher (EXPRES download UserGuide) . Although the datasets are available in the CSV format, the application is supported by Oracle 10g DBMS, and makes use ofATRE and SPADAsystems. For further details, please contact the project team persons.
Warning:The system EXPRES is free for evaluation, research and teaching purposes, but not for commercial purposes.
Project Leader Prof. Donato Malerba
LACAM Staff Corrado Loglisci
Students involved in the project Davide Coratza
(in inverse chronological order)
Last Update: Tue Apr 10 2007 14:21:36 GMT+0200 (ora legale Europa occidentale)
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