toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Record Links
Author (up) Alessandro Farasin; Paolo Garza pdf 
  Title PERCEIVE: Precipitation Data Characterization by means on Frequent Spatio-Temporal Sequences Type Conference Article
  Year 2018 Publication ISCRAM 2018 Conference Proceedings 15th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2018  
  Volume Issue Pages 1081-1088  
  Keywords Spatio-temporal sequence mining; Data characterization  
  Abstract Nowadays large amounts of climatology data, including daily precipitation data, are collected by means of sensors located in different locations of the world. The data driven analysis of these large data sets by means of scalable machine learning and data mining techniques allows extracting interesting knowledge from data, inferring interesting patterns and correlations among sets of spatio-temporal events and characterizing them. In this paper, we describe the PERCEIVE framework. PERCEIVE is a data-driven framework based on frequent spatio-temporal sequences and aims at extracting frequent correlations among spatio-temporal precipitation events. It is implemented by using R and Apache Spark, for scalability reasons, and provides also a visualization module that can be used to intuitively show the extracted patterns. A preliminary set of experiments show the efficiency and the effectiveness of PERCEIVE.  
  Address  
  Corporate Author Thesis  
  Publisher Rochester Institute of Technology Place of Publication Rochester, NY (USA) Editor Kees Boersma; Brian Tomaszewski  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-0-692-12760-5 Medium  
  Track 1st International Workshop on Intelligent Crisis Management Technologies for Climate Events (ICMT) Expedition Conference ISCRAM 2018 Conference Proceedings 15th International Conference on Information Systems for Crisis Response and Management  
  Notes paolo.garza@polito.it Approved no  
  Call Number Serial 1628  
Share this record to Facebook
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: