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A method for discovery and analysis of temporal patterns in complex event data / Donna J. Peuquet in International journal of geographical information science IJGIS, vol 29 n° 9 (September 2015)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 29 n° 9 (September 2015) . - pp 1588 - 1611 Titre : A method for discovery and analysis of temporal patterns in complex event data Type de document : Article/Communication Auteurs : Donna J. Peuquet, Auteur ; Anthony C. Robinson, Auteur ; Samuel Stehle, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1588 - 1611 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] découverte de connaissances [Termes IGN] données spatiotemporelles [Termes IGN] événement [Termes IGN] extension temporelle Mots-clés libres : T-pattern analysis  STempo Résumé : (Auteur) Pattern analysis techniques currently common within geography tend to focus either on characterizing patterns of spatial and/or temporal recurrence of a single event type (e.g., incidence of flu cases) or on comparing sequences of a limited number of event types where relationships between events are already represented in the data (e.g., movement patterns). The availability of large amounts of multivariate spatiotemporal data, however, requires new methods for pattern analysis. Here, we present a technique for finding associations among many different event types where the associations among these varying event types are not explicitly represented in the data or known in advance. This pattern discovery method, known as T-pattern analysis, was first developed within the field of psychology for the purpose of finding patterns in personal interactions. We have adapted and extended the T-pattern method to take the unique characteristics of geographic data into account and implemented it within a geovisualization toolkit for an integrated computational-geovisual environment we call STempo. To demonstrate how T-pattern analysis can be employed in geographic research for discovering patterns in complex spatiotemporal data, we describe a case study featuring events from news reports about Yemen during the Arab Spring of 2011–2012. Using supplementary data from the Global Database of Events, Language, and Tone, we briefly summarize and reference a separate validation study, then evaluate the scalability of the T-pattern approach. We conclude with ideas for further extensions of the T-pattern technique to increase its utility for spatiotemporal analysis. Numéro de notice : A2015-608 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1042380 En ligne : https://doi.org/10.1080/13658816.2015.1042380 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78037 [article]