Paru le : 01/06/2015 |
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Ajouter le résultat dans votre panierPoints of interest recommendation from GPS trajectories / Yaqiong Liu in International journal of geographical information science IJGIS, vol 29 n° 6 (June 2015)
[article]
Titre : Points of interest recommendation from GPS trajectories Type de document : Article/Communication Auteurs : Yaqiong Liu, Auteur ; Hock Soon Seah, Auteur Année de publication : 2015 Article en page(s) : pp 953-979 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse de groupement
[Termes IGN] calcul d'itinéraire
[Termes IGN] point d'intérêt
[Termes IGN] positionnement par GPS
[Termes IGN] regroupement de données
[Termes IGN] trajet (mobilité)
[Termes IGN] utilisateur nomade
[Termes IGN] visualisation simultanéeRésumé : (Auteur) Recently, points of interest (POIs) recommendation has evolved into a hot research topic with real-world applications. In this paper, we propose a novel semantics-enhanced density-based clustering algorithm SEM-DTBJ-Cluster, to extract semantic POIs from GPS trajectories. We then take into account three different factors (popularity, temporal and geographical features) that can influence the recommendation score of a POI. We characterize the impacts caused by popularity, temporal and geographical information, by using different scoring functions based on three developed recommendation models. Finally, we combine the three scoring functions together and obtain a unified framework PTG-Recommend for recommending candidate POIs for a mobile user. To the best of our knowledge, this work is the first that considers popularity, temporal and geographical information together. Experimental results on two real-world data sets strongly demonstrate that our framework is robust and effective, and outperforms the baseline recommendation methods in terms of precision and recall. Numéro de notice : A2015-597 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1005094 En ligne : https://doi.org/10.1080/13658816.2015.1005094 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78011
in International journal of geographical information science IJGIS > vol 29 n° 6 (June 2015) . - pp 953-979[article]Integrative representation and inference of qualitative locations about points, lines, and polygons / Shihong Du in International journal of geographical information science IJGIS, vol 29 n° 6 (June 2015)
[article]
Titre : Integrative representation and inference of qualitative locations about points, lines, and polygons Type de document : Article/Communication Auteurs : Shihong Du, Auteur ; Chen-Chieh Feng, Auteur ; Luo Guo, Auteur Année de publication : 2015 Article en page(s) : pp 980-1006 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] figure géométrique
[Termes IGN] positionnement automatique
[Termes IGN] primitive géométrique
[Termes IGN] raisonnement spatial
[Termes IGN] relation spatiale
[Termes IGN] relation topologique
[Termes IGN] représentation cartographiqueRésumé : (Auteur) Qualitative knowledge representation of spatial locations and relations is popular in many text-based media, for example, postings on social networks, news reports, and encyclopedia, as representing qualitative spatial locations is indispensable to infer spatial knowledge from them. However, an integrative model capable of handling direction-based locations of various spatial objects is missing. This study presents an integrative representation and inference framework about direction-based qualitative locations for points, lines, and polygons. In the framework, direction partitions of different types of reference objects are first unified to create a partition consisting of cells, segments, and corners. They serve as a frame of reference to locate spatial objects (e.g., points, lines, and polygons). Qualitative relations are then defined to relate spatial objects to the elements in a cell partition, and to form the model of qualitative locations. Last, based on the integrative representation, location-based reasoning mechanism is presented to derive topological relations between objects from their locations, such as point–point, line–line, point–line, point–polygon, line–polygon, and polygon–polygon relations. The presented model can locate any type of spatial objects in a frame of reference composed of points, lines, and polygons, and derive topological relations between any pairs of objects from the locations in a unified method. Numéro de notice : A2015-598 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1004333 En ligne : https://doi.org/10.1080/13658816.2015.1004333 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78012
in International journal of geographical information science IJGIS > vol 29 n° 6 (June 2015) . - pp 980-1006[article]Multi-label class assignment in land-use modelling / Hichem Omrani in International journal of geographical information science IJGIS, vol 29 n° 6 (June 2015)
[article]
Titre : Multi-label class assignment in land-use modelling Type de document : Article/Communication Auteurs : Hichem Omrani, Auteur ; Fahed Abdallah, Auteur ; Omar Charif, Auteur Année de publication : 2015 Article en page(s) : pp 1023 - 1041 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] alignement semi-dirigé
[Termes IGN] analyse multivariée
[Termes IGN] apprentissage automatique
[Termes IGN] classification barycentrique
[Termes IGN] image aérienne
[Termes IGN] Luxembourg
[Termes IGN] modélisation
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] utilisation du solRésumé : (Auteur) During the last two decades, a variety of models have been applied to understand and predict changes in land use. These models assign a single-attribute label to each spatial unit at any particular time of the simulation. This is not realistic because mixed use of land is quite common. A more detailed classification allowing the modelling of mixed land use would be desirable for better understanding and interpreting the evolution of the use of land. A possible solution is the multi-label (ML) concept where each spatial unit can belong to multiple classes simultaneously. For example, a cluster of summer houses at a lake in a forested area should be classified as water, forest and residential (built-up). The ML concept was introduced recently, and it belongs to the machine learning field. In this article, the ML concept is introduced and applied in land-use modelling. As a novelty, we present a land-use change model that allows ML class assignment using the k nearest neighbour (kNN) method that derives a functional relationship between land use and a set of explanatory variables. A case study with a rich data-set from Luxembourg using biophysical data from aerial photography is described. The model achieves promising results based on the well-known ML evaluation criteria. The application described in this article highlights the value of the multi-label k nearest neighbour method (MLkNN) for land-use modelling. Numéro de notice : A2015-599 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1008004 En ligne : https://doi.org/10.1080/13658816.2015.1008004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78013
in International journal of geographical information science IJGIS > vol 29 n° 6 (June 2015) . - pp 1023 - 1041[article]