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Towards fusing uncertain location data from heterogeneous sources / Bing Zhang in Geoinformatica, vol 20 n° 2 (April - June 2016)  

Public [article]  inGeoinformatica > vol 20 n° 2 (April - June 2016) . - pp 179 - 212 Titre : Towards fusing uncertain location data from heterogeneous sources Type de document : Article/Communication Auteurs : Bing Zhang, Auteur ; Goce Trajcevski, Auteur ; Liu Liu, Auteur Année de publication : 2016 Article en page(s) : pp 179 - 212 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] appareil portable [Termes IGN] capteur passif [Termes IGN] données localisées [Termes IGN] données spatiotemporelles [Termes IGN] fusion de données [Termes IGN] incertitude de position [Termes IGN] objet mobile [Termes IGN] requête spatiotemporelle [Termes IGN] traitement de données localisées Résumé : (auteur) Properly incorporating location-uncertainties – which is, fully considering their impact when processing queries of interest – is a paramount in any application dealing with spatio-temporal data. Typically, the location-uncertainty is a consequence of the fact that objects cannot be tracked continuously and the inherent imprecision of localization devices. Although there is a large body of works tackling various aspects of efficient management of uncertainty in spatio-temporal data – the settings consider homogeneous localization devices, e.g., either a Global Positioning System (GPS), or different sensors (roadside, indoor, etc.). In this work, we take a first step towards combining the uncertain location data – i.e., fusing the uncertainty of moving objects location – obtained from both GPS devices and roadside sensors. We develop a formal model for capturing the whereabouts in time in this setting and propose the Fused Bead (FB) model, extending the bead model based solely on GPS locations. We also present algorithms for answering traditional spatio-temporal range queries, as well as a special variant pertaining to objects locations with respect to lanes on road segments – augmenting the conventional graph based road network with the width attribute. In addition, pruning techniques are proposed in order to expedite the query processing. We evaluated the benefits of the proposed approach on both real (Beijing taxi) and synthetic (generated from a customized trajectory generator) data. Our experiments demonstrate that the proposed method of fusing the uncertainties may eliminate up to 26 % of the false positives in the Beijing taxi data, and up to 40 % of the false positives in the larger synthetic dataset, when compared to using the traditional bead uncertainty models. Numéro de notice : A2016-371 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-015-0238-6 En ligne : http://dx.doi.org/10.1007/s10707-015-0238-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81133 [article]

Towards sustainable mobility behavior: research challenges for location-aware information and communication technology / Paul Weiser in Geoinformatica, vol 20 n° 2 (April - June 2016)  

Public [article]  inGeoinformatica > vol 20 n° 2 (April - June 2016) . - pp 213 - 239 Titre : Towards sustainable mobility behavior: research challenges for location-aware information and communication technology Type de document : Article/Communication Auteurs : Paul Weiser, Auteur ; Simon Scheider, Auteur ; Dominik Bucher, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 213 - 239 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] approche participative [Termes IGN] changement climatique [Termes IGN] comportement [Termes IGN] développement durable [Termes IGN] état de l'art [Termes IGN] innovation technologique [Termes IGN] mobilité humaine [Termes IGN] positionnement cinématique [Termes IGN] système d'information géographique [Termes IGN] téléphonie mobile [Termes IGN] transport Résumé : (auteur) Private transport accounts for a large amount of total CO2 emissions, thus significantly contributing to global warming. Tools that actively support people in engaging in a more sustainable life-style without restricting their mobility are urgently needed. How can location-aware information and communication technology (ICT) enable novel interactive and participatory approaches that help people in becoming more sustainable? In this survey paper, we discuss the different aspects of this challenge from a technological and cognitive engineering perspective, based on an overview of the main information processes that may influence mobility behavior. We review the state-of-the-art of research with respect to various ways of influencing mobility behavior (e.g., through providing real-time, user-specific, and location-based feedback) and suggest a corresponding research agenda. We conclude that future research has to focus on reflecting individual goals in providing personal feedback and recommendations that take into account different motivational stages. In addition, a long-term and large-scale empirical evaluation of such tools is necessary. Numéro de notice : A2016-372 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.1007/s10707-015-0242-x En ligne : http://dx.doi.org/10.1007/s10707-015-0242-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81137 [article]

Advanced methods for the estimation of an unknown projection from a map / Tomáš Bayer in Geoinformatica, vol 20 n° 2 (April - June 2016)  

Public [article]  inGeoinformatica > vol 20 n° 2 (April - June 2016) . - pp 241 - 284 Titre : Advanced methods for the estimation of an unknown projection from a map Type de document : Article/Communication Auteurs : Tomáš Bayer, Auteur Année de publication : 2016 Article en page(s) : pp 241 - 284 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Projections [Termes IGN] constante [Termes IGN] distribution spatiale [Termes IGN] géoréférencement [Termes IGN] ligne caractéristique [Termes IGN] logiciel de calcul scientifique [Termes IGN] système de projection Résumé : (auteur) This article presents three new methods (M5, M6, M7) for the estimation of an unknown map projection and its parameters. Such an analysis is beneficial and interesting for historic, old, or current maps without information about the map projection; it could improve their georeference. The location similarity approach takes into account the residuals on the corresponding features; the minimum is found using the non-linear least squares. For the shape similarity approach, the minimized objective function ϕ takes into account the spatial distribution of the features, together with the shapes of the meridians, parallels and other 0D-2D elements. Due to the non-convexity and discontinuity, its global minimum is determined using the global optimization, represented by the differential evolution. The constant values of projection φ k , λ k , φ 1, λ 0, and map constants R,ΔX,ΔY, α (in relation to which the methods are invariant) are estimated. All methods are compared and the results are presented for the synthetic data as well as for 8 early maps from the Map Collection of the Charles University and the David Rumsay Map Collection. The proposed algorithms have been implemented in the new version of the detectproj software. Numéro de notice : A2016-373 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.1007/s10707-015-0234-x En ligne : http://dx.doi.org/10.1007/s10707-015-0234-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81138 [article]

A framework for intelligence analysis using spatio-temporal storytelling / Raimundo F. Dos Santos Jr. in Geoinformatica, vol 20 n° 2 (April - June 2016)  

Public [article]  inGeoinformatica > vol 20 n° 2 (April - June 2016) . - pp 285 - 326 Titre : A framework for intelligence analysis using spatio-temporal storytelling Type de document : Article/Communication Auteurs : Raimundo F. Dos Santos Jr., Auteur ; Sumit Shah, Auteur ; Arnold Boedihardjo, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 285 - 326 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] diffusion de l'information [Termes IGN] dimension temporelle [Termes IGN] données spatiotemporelles [Termes IGN] graphe [Termes IGN] information complexe [Termes IGN] réseau social Résumé : (auteur) Social media have ushered in alternative modalities to propagate news and developments rapidly. Just as traditional IR matured to modeling storylines from search results, we are now at a point to study how stories organize and evolve in additional mediums such as Twitter, a new frontier for intelligence analysis. This study takes as input news articles as well as social media feeds and extracts and connects entities into interesting storylines not explicitly stated in the underlying data. First, it proposes a novel method of spatio-temporal analysis on induced concept graphs that models storylines propagating through spatial regions in a time sequence. Second, it describes a method to control search space complexity by providing regions of exploration. And third, it describes ConceptRank as a ranking strategy that differentiates strongly-typed connections from weakly-bound ones. Extensive experiments on the Boston Marathon Bombings of April 15, 2013 as well as socio-political and medical events in Latin America, the Middle East, and the United States demonstrate storytelling’s high application potential, showcasing its use in event summarization and association analysis that identifies events before they hit the newswire. Numéro de notice : A2016-374 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.1007/s10707-015-0236-8 En ligne : http://dx.doi.org/10.1007/s10707-015-0236-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81139 [article]

Exploring cell tower data dumps for supervised learning-based point-of-interest prediction (industrial paper) / Ran Wang in Geoinformatica, vol 20 n° 2 (April - June 2016)  

Public [article]  inGeoinformatica > vol 20 n° 2 (April - June 2016) . - pp 327 - 349 Titre : Exploring cell tower data dumps for supervised learning-based point-of-interest prediction (industrial paper) Type de document : Article/Communication Auteurs : Ran Wang, Auteur ; Chi-Yin Chow, Auteur ; Yan Lyu, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 327 - 349 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] algorithme d'apprentissage [Termes IGN] apprentissage dirigé [Termes IGN] comportement [Termes IGN] données massives [Termes IGN] exploration de données [Termes IGN] histogramme [Termes IGN] point d'intérêt [Termes IGN] positionnement automatique [Termes IGN] téléphonie mobile [Termes IGN] utilisateur Résumé : (auteur) Exploring massive mobile data for location-based services becomes one of the key challenges in mobile data mining. In this paper, we investigate a problem of finding a correlation between the collective behavior of mobile users and the distribution of points of interest (POIs) in a city. Specifically, we use large-scale cell tower data dumps collected from cell towers and POIs extracted from a popular social network service, Weibo. Our objective is to make use of the data from these two different types of sources to build a model for predicting the POI densities of different regions in the covered area. An application domain that may benefit from our research is a business recommendation application, where a prediction result can be used as a recommendation for opening a new store/branch. The crux of our contribution is the method of representing the collective behavior of mobile users as a histogram of connection counts over a period of time in each region. This representation ultimately enables us to apply a supervised learning algorithm to our problem in order to train a POI prediction model using the POI data set as the ground truth. We studied 12 state-of-the-art classification and regression algorithms; experimental results demonstrate the feasibility and effectiveness of the proposed method. Numéro de notice : A2016-375 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Article DOI : 10.1007/s10707-015-0237-7 En ligne : http://dx.doi.org/10.1007/s10707-015-0237-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81140 [article]