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Mining and visual exploration of closed contiguous sequential patterns in trajectories / Can Yang in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 32 n° 7-8 (July - August 2018) . - pp 1413 - 1435 Titre : Mining and visual exploration of closed contiguous sequential patterns in trajectories Type de document : Article/Communication Auteurs : Can Yang, Auteur ; Gyözö Gidofalvi, Auteur Année de publication : 2018 Article en page(s) : pp 1413 - 1435 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse spatio-temporelle [Termes IGN] arbre de décision [Termes IGN] exploration de données géographiques [Termes IGN] réseau routier [Termes IGN] trafic routier [Termes IGN] trajectoire (véhicule non spatial) [Termes IGN] visualisation de données [Vedettes matières IGN] Géovisualisation Mots-clés libres : closed contiguous sequential pattern = motif séquentiel contigu fermé Résumé : (auteur) Large collections of trajectories provide rich insight into movement patterns of the tracked objects. By map matching trajectories to a road network as sequences of road edge IDs, contiguous sequential patterns can be extracted as a certain number of objects traversing a specific path, which provides valuable information in travel demand modeling and transportation planning. Mining and visualization of such patterns still face challenges in efficiency, scalability, and visual cluttering of patterns. To address these challenges, this article firstly proposes a Bidirectional Pruning based Closed Contiguous Sequential pattern Mining (BP-CCSM) algorithm. By employing tree structures to create partitions of input sequences and candidate patterns, closeness can be checked efficiently by comparing nodes in a tree. Secondly, a system called Sequential Pattern Explorer for Trajectories (SPET) is built for spatial and temporal exploration of the mined patterns. Two types of maps are designed where a conventional traffic map gives an overview of the movement patterns and a dynamic offset map presents detailed information according to user-specified filters. Extensive experiments are performed in this article. BP-CCSM is compared with three other state-of-the-art algorithms on two datasets: a small public dataset containing clickstreams from an e-commerce and a large global positioning system dataset with more than 600,000 taxi trip trajectories. The results show that BP-CCSM considerably outperforms three other algorithms in terms of running time and memory consumption. Besides, SPET provides an efficient and convenient way to inspect spatial and temporal variations in closed contiguous sequential patterns from a large number of trajectories. Numéro de notice : A2018-279 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2017.1393542 Date de publication en ligne : 31/10/2017 En ligne : https://doi.org/10.1080/13658816.2017.1393542 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90361 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2018041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Measures of transport mode segmentation of trajectories / Adrain C. Prelipcean in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 1763 - 1805 Titre : Measures of transport mode segmentation of trajectories Type de document : Article/Communication Auteurs : Adrain C. Prelipcean, Auteur ; Gyözö Gidofalvi, Auteur ; Yusak O. Susilo, Auteur Année de publication : 2016 Article en page(s) : pp 1763 - 1805 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse diachronique [Termes IGN] analyse spatio-temporelle [Termes IGN] calcul d'erreur [Termes IGN] itinéraire [Termes IGN] navigation [Termes IGN] segmentation [Termes IGN] transport Résumé : (Auteur) Rooted in the philosophy of point- and segment-based approaches for transportation mode segmentation of trajectories, the measures that researchers have adopted to evaluate the quality of the results (1) are incomparable across approaches, hence slowing the progress in the field and (2) do not provide insight about the quality of the continuous transportation mode segmentation. To address these problems, this paper proposes new error measures that can be applied to measure how well a continuous transportation mode segmentation model performs. The error measures introduced are based on aligning multiple inferred continuous intervals to ground truth intervals, and measure the cardinality of the alignment and the spatial and temporal discrepancy between the corresponding aligned segments. The utility of this new way of computing errors is shown by evaluating the segmentation of three generic transportation mode segmentation approaches (implicit, explicit–holistic, and explicit–consensus-based transport mode segmentation), which can be implemented in a thick client architecture. Empirical evaluations on a large real-word data set reveal the superiority of explicit–consensus-based transport mode segmentation, which can be attributed to the explicit modeling of segments and transitions, which allows for a meaningful decomposition of the complex learning task. Numéro de notice : A2016-568 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1137297 Date de publication en ligne : 29/01/2016 En ligne : http://dx.doi.org/10.1080/13658816.2015.1137297 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81712 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2016051	RAB	Revue	Centre de documentation	En réserve L003	Disponible