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Contextual location recommendation for location-based social networks by learning user intentions and contextual triggers / Seyyed Mohammadreza Rahimi in Geoinformatica, vol 26 n° 1 (January 2022)
[article]
Titre : Contextual location recommendation for location-based social networks by learning user intentions and contextual triggers Type de document : Article/Communication Auteurs : Seyyed Mohammadreza Rahimi, Auteur ; Behrouz Far, Auteur ; Xin Wang, Auteur Année de publication : 2022 Article en page(s) : pp 1 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse spatiale
[Termes IGN] comportement
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] covariance
[Termes IGN] données spatiotemporelles
[Termes IGN] historique des données
[Termes IGN] interface web
[Termes IGN] mobilité territoriale
[Termes IGN] prise en compte du contexte
[Termes IGN] réseau social géodépendant
[Termes IGN] service fondé sur la position
[Termes IGN] système de recommandationRésumé : (auteur) Location recommendation methods suggest unvisited locations to their users. Many existing location recommendation methods focus on the spatial, social and temporal aspects of human movements. However, contextual information is also invaluable to location recommendation methods and has the great potential for explaining what triggers users to show different behaviors. CLR learns the response of the users to contextual variables based on their own history and the history of similar behaving users. In this paper, we propose a contextual location recommendation method named Contextual Location Recommendation (CLR) that learns the intention and spatial responses of users to various contextual triggers using the historical check-in and contextual information. CLR starts with a co-variance analysis to reduce dimensionality of the check-in data and then uses an optimized version of the random walk with restart to extract hidden user responses to contextual triggers. A tensor factorization is used to build a latent-factor model to predict the user’s intention response with the given set of contextual triggers. Based on the intention response of the user, a contextual spatial component identifies a set of matching locations accessible to the user by estimating the probability distribution of the location of the user and the popularity probability of locations under the contextual settings. Experimental results on three real-world datasets show that CLR improves the recommendation precision by 35% compared to the best-performing baseline recommendation method. Numéro de notice : A2022-203 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-021-00437-y Date de publication en ligne : 02/06/2021 En ligne : https://doi.org/10.1007/s10707-021-00437-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100008
in Geoinformatica > vol 26 n° 1 (January 2022) . - pp 1 - 28[article]Generating geographical location descriptions with spatial templates: a salient toponym driven approach / Mark M. Hall in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)
[article]
Titre : Generating geographical location descriptions with spatial templates: a salient toponym driven approach Type de document : Article/Communication Auteurs : Mark M. Hall, Auteur ; Christopher B. Jones, Auteur Année de publication : 2022 Article en page(s) : pp 55 - 85 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Toponymie
[Termes IGN] image Flickr
[Termes IGN] OpenStreetMap
[Termes IGN] relation spatiale
[Termes IGN] répertoire toponymique
[Termes IGN] saillance
[Termes IGN] toponyme
[Termes IGN] traitement du langage naturelRésumé : (auteur) Natural language descriptions of geographical locations are used frequently in daily life and there is a motivation to create systems that generate such descriptions automatically, for purposes such as documentation of where events have taken place, where a person is located, where photos were taken and where plants and animals are located. Typically location descriptions combine references to named geographical features with vague spatial relational terms, such as near, north of and at that relate locations to the features. Here we describe a system for generating location descriptions, that combines spatial templates, that model the applicability of different spatial relations relative to a reference location, with toponyms in the vicinity of the described location that are selected according to aspects of salience. The toponyms are retrieved from a gazetteer service based on OpenStreetMap for which we create a hierarchical feature classification scheme to facilitate selection of toponyms according to distinctiveness of their feature types and other aspects of salience. The advantages of the approach are demonstrated in a user study, relative to an existing state of the art system and to other baseline approaches that include manually created captions and the automated methods of two widely used photo captioning systems. Numéro de notice : A2022-043 Affiliation des auteurs : non IGN Thématique : TOPONYMIE Nature : Article DOI : 10.1080/13658816.2021.1913498 Date de publication en ligne : 28/04/2021 En ligne : https://doi.org/10.1080/13658816.2021.1913498 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99402
in International journal of geographical information science IJGIS > vol 36 n° 1 (January 2022) . - pp 55 - 85[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2022011 SL Revue Centre de documentation Revues en salle Disponible A semantics-based trajectory segmentation simplification method / Minshi Liu in Journal of Geovisualization and Spatial Analysis, vol 5 n° 2 (December 2021)
[article]
Titre : A semantics-based trajectory segmentation simplification method Type de document : Article/Communication Auteurs : Minshi Liu, Auteur ; Guifang He, Auteur ; Yi Long, Auteur Année de publication : 2021 Article en page(s) : n° 19 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] caractérisation
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] itinéraire
[Termes IGN] précision sémantique
[Termes IGN] simplification de contourRésumé : (auteur) With the development of mobile positioning technology, a large amount of mobile trajectory data has been generated. Therefore, to store, process and mine trajectory data in a better way, trajectory data simplification is imperative. Current trajectory data simplification methods are either based on spatiotemporal features or semantic features, such as road network structure, but they do not consider semantic features of a trajectory stop. To overcome this limitation, this study presents a trajectory segmentation simplification method based on stop features. The proposed method first extracts the stop feature of a trajectory, then divides the trajectory into move segments and stop segments based on the stop features, and finally simplifies the obtained segments. The proposed method is verified by experiments on personal trajectory data and taxi trajectory data. Compared with the classic spatiotemporal simplification method, the proposed method has higher spatiotemporal and semantic accuracy under different simplification scales. The proposed method is especially suitable for trajectory data with more stop features. Numéro de notice : A2021-970 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s41651-021-00088-5 Date de publication en ligne : 27/09/2021 En ligne : http://dx.doi.org/10.1007/s41651-021-00088-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100367
in Journal of Geovisualization and Spatial Analysis > vol 5 n° 2 (December 2021) . - n° 19[article]Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions / Haosheng Huang in Computers, Environment and Urban Systems, vol 90 (November 2021)
[article]
Titre : Analytics of location-based big data for smart cities: Opportunities, challenges, and future directions Type de document : Article/Communication Auteurs : Haosheng Huang, Auteur ; Xiaobai Yao, Auteur ; Jukka Mathias Krisp, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 101712 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] données massives
[Termes IGN] planification urbaine
[Termes IGN] service fondé sur la position
[Termes IGN] téléphonie mobile
[Termes IGN] ville durable
[Termes IGN] ville intelligenteRésumé : (auteur) The growing ubiquity of location/activity sensing technologies and location-based services (LBS) has led to a large volume and variety of location-based big data (LocBigData), such as location tracking or sensing data, social media data, and crowdsourced geographic information. The increasing availability of such LocBigData has created unprecedented opportunities for research on urban systems and human environments in general. In this article, we first review the common types of LocBigData: mobile phone network data, GPS data, Location-based social media data, LBS usage/log data, smart card travel data, beacon log data (WiFi or Bluetooth), and camera imagery data. Secondly, we describe the opportunities fueled by LocBigData for the realization of smart cities, mainly via answering questions ranging from “what happened” and “why did it happen” to “what's likely to happen in the future” and “what to do next”. Thirdly, pitfalls of dealing with LocBigData are summarized, such as high volume/velocity/variety; non-random sampling; messy and not clean data; and correlations rather than causal relationships. Finally, we review the state-of-the-art research trends in this field, and conclude the article with a list of open research challenges and a research agenda for LocBigData research to help achieve the vision of smart and sustainable cities. Numéro de notice : A2021-650 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101712 Date de publication en ligne : 08/09/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101712 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98368
in Computers, Environment and Urban Systems > vol 90 (November 2021) . - n° 101712[article]Point-of-interest (POI) data validation methods: An urban case study / Lih Wei Yeow in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)
[article]
Titre : Point-of-interest (POI) data validation methods: An urban case study Type de document : Article/Communication Auteurs : Lih Wei Yeow, Auteur ; Raymond Low, Auteur ; Yu Xiang Tan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 735 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse spatiale
[Termes IGN] données cartographiques
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] erreur de positionnement
[Termes IGN] OpenStreetMap
[Termes IGN] point d'intérêt
[Termes IGN] qualité des données
[Termes IGN] Singapour
[Termes IGN] validation des donnéesRésumé : (auteur) Point-of-interest (POI) data from map sources are increasingly used in a wide range of applications, including real estate, land use, and transport planning. However, uncertainties in data quality arise from the fact that some of this data are crowdsourced and proprietary validation workflows lack transparency. Comparing data quality between POI sources without standardized validation metrics is a challenge. This study reviews and implements the available POI validation methods, working towards identifying a set of metrics that is applicable across datasets. Twenty-three validation methods were found and categorized. Most methods evaluated positional accuracy, while logical consistency and usability were the least represented. A subset of nine methods was implemented to assess four real-world POI datasets extracted for a highly urbanized neighborhood in Singapore. The datasets were found to have poor completeness with errors of commission and omission, although spatial errors were reasonably low ( Numéro de notice : A2021-830 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10110735 Date de publication en ligne : 29/10/2021 En ligne : https://doi.org/10.3390/ijgi10110735 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98968
in ISPRS International journal of geo-information > vol 10 n° 11 (November 2021) . - n° 735[article]The geography of social media data in urban areas: Representativeness and complementarity / Alvaro Bernabeu-Bautista in ISPRS International journal of geo-information, vol 10 n° 11 (November 2021)PermalinkA topic model based framework for identifying the distribution of demand for relief supplies using social media data / Ting Zhang in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)PermalinkUrban land-use analysis using proximate sensing imagery: a survey / Zhinan Qiao in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)PermalinkDisaster Image Classification by Fusing Multimodal Social Media Data / Zhiqiang Zou in ISPRS International journal of geo-information, vol 10 n° 10 (October 2021)PermalinkUnderstanding the modifiable areal unit problem in dockless bike sharing usage and exploring the interactive effects of built environment factors / Feng Gao in International journal of geographical information science IJGIS, vol 35 n° 9 (September 2021)PermalinkPredicting user activity intensity using geographic interactions based on social media check-in data / Jing Li in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)PermalinkIdentifying home locations in human mobility data: an open-source R package for comparison and reproducibility / Qingqing Chen in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)PermalinkConstructing and analyzing spatial-social networks from location-based social media data / Xuebin Wei in Cartography and Geographic Information Science, vol 48 n° 3 (May 2021)PermalinkUnderstanding collective human movement dynamics during large-scale events using big geosocial data analytics / Junchuan Fan in Computers, Environment and Urban Systems, vol 87 (May 2021)PermalinkStop-and-move sequence expressions over semantic trajectories / Yenier Torres Izquierdo in International journal of geographical information science IJGIS, vol 35 n° 4 (April 2021)PermalinkUtilizing urban geospatial data to understand heritage attractiveness in Amsterdam / Sevim Sezi Karayazi in ISPRS International journal of geo-information, vol 10 n° 4 (April 2021)PermalinkLearning from GPS trajectories of floating car for CNN-based urban road extraction with high-resolution satellite imagery / Ju Zhang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)PermalinkDetection of pictorial map objects with convolutional neural networks / Raimund Schnürer in Cartographic journal (the), vol 58 n° 1 (February 2021)PermalinkJoint promotion partner recommendation systems using data from location-based social networks / Yi-Chung Chen in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)PermalinkChinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data / Yunhao Zheng in Computers, Environment and Urban Systems, vol 85 (January 2021)PermalinkIntroducing diversion graph for real-time spatial data analysis with location based social networks / Sameera Kannangara (2021)PermalinkPermalinkExploring the heterogeneity of human urban movements using geo-tagged tweets / Ding Ma in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)PermalinkHow urban places are visited by social groups? Evidence from matrix factorization on mobile phone data / Chaogui Kang in Transactions in GIS, Vol 24 n° 6 (December 2020)PermalinkSocial media as passive geo-participation in transportation planning – how effective are topic modeling & sentiment analysis in comparison with citizen surveys? / Oliver Lock in Geo-spatial Information Science, vol 23 n° 4 (December 2020)Permalink