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Author  |
Alessandro Farasin; Paolo Garza |
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Title |
PERCEIVE: Precipitation Data Characterization by means on Frequent Spatio-Temporal Sequences |
Type |
Conference Article |
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Year |
2018 |
Publication |
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2018 |
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Volume |
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Issue |
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Pages |
1081-1088 |
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Keywords |
Spatio-temporal sequence mining, Data characterization |
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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. |
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Publisher |
Rochester Institute of Technology |
Place of Publication |
Rochester, NY (USA) |
Editor |
Kees Boersma; Brian Tomaszeski |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Title |
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Series Volume |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-0-692-12760-5 |
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Track |
1st International Workshop on Intelligent Crisis Management Technologies for Climate Events (ICMT) |
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Conference |
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
2180 |
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Author |
Frédérick Bénaben; Chihab Hanachi; Matthieu Lauras; Pierre Couget; Vincent Chapurlat |
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Title |
A metamodel and its ontology to guide crisis characterization and its collaborative management |
Type |
Conference Article |
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Year |
2008 |
Publication |
Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2008 |
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Volume |
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Issue |
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Pages |
189-196 |
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Keywords |
Characterization; Hardware; Ontology; Automated reasoning; Collaborative management; Collaborative process; Crisis; Crisis management; Metamodeling; Reference modeling; System of systems; Information systems |
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Abstract |
This paper presents a research in progress about the French ISyCri project that aims at providing partners involved in crisis management with an agile Mediation Information System (MIS). Not only this MIS shoul support the interoperability of the partners' information systems but it is also dedicated to coordinate their activities through a collaborative process. One of the first and main steps towards such a MIS, is to elaborate a common and sharable reference model built to characterize crisis situations. Such a model is also an input for automated reasoning to elaborate and adapt a crisis solving collaborative process. This article presents the objective of the project, our approach and our first results: a UML metamodel of crisis situation and its corresponding OWL ontology on top of which deductions are possible. |
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Address |
Université de Toulouse, Mines ALBI, DR/GI, France; Université de Toulouse 1, France; Prefecture du Tarn, France; Ecole des Mines D'Alès, LGI2P, France |
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Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Washington, DC |
Editor |
F. Fiedrich, B. Van de Walle |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Volume |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780615206974 |
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Track |
Ontologies for Crisis Management |
Expedition |
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Conference |
5th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
301 |
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