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Recommendations in location-based social networks: a survey / Jie Bao in Geoinformatica, vol 19 n° 3 (July - September 2015)
[article]
Titre : Recommendations in location-based social networks: a survey Type de document : Article/Communication Auteurs : Jie Bao, Auteur ; David Wilkie, Auteur ; Mohamed Mokbe, Auteur Année de publication : 2015 Article en page(s) : pp 525 - 565 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse comparative
[Termes IGN] analyse de données
[Termes IGN] géobalise
[Termes IGN] performance
[Termes IGN] positionnement automatique
[Termes IGN] réseau social géodépendant
[Termes IGN] source de données
[Termes IGN] système de recommandation
[Termes IGN] utilisateurRésumé : (auteur) Recent advances in localization techniques have fundamentally enhanced social networking services, allowing users to share their locations and location-related contents, such as geo-tagged photos and notes. We refer to these social networks as location-based social networks (LBSNs). Location data bridges the gap between the physical and digital worlds and enables a deeper understanding of users’ preferences and behavior. This addition of vast geo-spatial datasets has stimulated research into novel recommender systems that seek to facilitate users’ travels and social interactions. In this paper, we offer a systematic review of this research, summarizing the contributions of individual efforts and exploring their relations. We discuss the new properties and challenges that location brings to recommender systems for LBSNs. We present a comprehensive survey analyzing 1) the data source used, 2) the methodology employed to generate a recommendation, and 3) the objective of the recommendation. We propose three taxonomies that partition the recommender systems according to the properties listed above. First, we categorize the recommender systems by the objective of the recommendation, which can include locations, users, activities, or social media. Second, we categorize the recommender systems by the methodologies employed, including content-based, link analysis-based, and collaborative filtering-based methodologies. Third, we categorize the systems by the data sources used, including user profiles, user online histories, and user location histories. For each category, we summarize the goals and contributions of each system and highlight the representative research effort. Further, we provide comparative analysis of the recommender systems within each category. Finally, we discuss the available data-sets and the popular methods used to evaluate the performance of recommender systems. Finally, we point out promising research topics for future work. This article presents a panorama of the recommender systems in location-based social networks with a balanced depth, facilitating research into this important research theme. Numéro de notice : A2015-497 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-014-0220-8 Date de publication en ligne : 06/02/2015 En ligne : https://doi.org/10.1007/s10707-014-0220-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77309
in Geoinformatica > vol 19 n° 3 (July - September 2015) . - pp 525 - 565[article]An inference-based framework to manage data provenance in geoscience applications / Mohammad Rezwanul Huq in IEEE Transactions on geoscience and remote sensing, vol 51 n° 11 (November 2013)
[article]
Titre : An inference-based framework to manage data provenance in geoscience applications Type de document : Article/Communication Auteurs : Mohammad Rezwanul Huq, Auteur ; Peter M.G. Apers, Auteur ; Andreas Wombacher, Auteur Année de publication : 2013 Article en page(s) : pp 5113 - 5130 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] flux de travaux
[Termes IGN] inférence
[Termes IGN] moteur d'inférence
[Termes IGN] source de données
[Termes IGN] synergiciel
[Termes IGN] traitement de données localiséesRésumé : (Auteur) Data provenance allows scientists to validate their model as well as to investigate the origin of an unexpected value. Furthermore, it can be used as a replication recipe for output data products. However, capturing provenance requires enormous effort by scientists in terms of time and training. First, they need to design the workflow of the scientific model, i.e., workflow provenance, which requires both time and training. However, in practice, scientists may not document any workflow provenance before the model execution due to the lack of time and training. Second, they need to capture provenance while the model is running, i.e., fine-grained data provenance. Explicit documentation of fine-grained provenance is not feasible because of the massive storage consumption by provenance data in the applications, including those from the geoscience domain where data are continuously arriving and are processed. In this paper, we propose an inference-based framework, which provides both workflow and fine-grained data provenance at a minimal cost in terms of time, training, and disk consumption. Our proposed framework is applicable to any given scientific model, and is capable of handling different model dynamics, such as variation in the processing time as well as input data products arrival pattern. Our evaluation of the framework in a real use case with geospatial data shows that the proposed framework is relevant and suitable for scientists in geoscientific domain. Numéro de notice : A2013-613 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2247769 En ligne : https://doi.org/10.1109/TGRS.2013.2247769 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32749
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 11 (November 2013) . - pp 5113 - 5130[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013111 RAB Revue Centre de documentation En réserve L003 Disponible Geoscience data provenance : An overview / Liping Di in IEEE Transactions on geoscience and remote sensing, vol 51 n° 11 (November 2013)
[article]
Titre : Geoscience data provenance : An overview Type de document : Article/Communication Auteurs : Liping Di, Auteur ; Peng Yue, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 5065 - 5072 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] acquisition de données
[Termes IGN] cyberinfrastructure
[Termes IGN] données localisées
[Termes IGN] état de l'art
[Termes IGN] processus spatio-temorel
[Termes IGN] service web
[Termes IGN] source de données
[Termes IGN] utilisateurRésumé : (Auteur) The advancement of Earth observing sensors, data, and information systems enhances significantly the capabilities to access and process large volumes of geoscience data, which are often consumed by scientific workflows and processed in a distributed information environment. Consequently, data provenance becomes important since it allows users to determine the usability and reliability of data products. Motivation for capturing and sharing provenance also comes from the distributed data and information infrastructure that has been benefiting the Earth science community in the past decade, such as spatial data and information infrastructure, e-Science, and cyberinfrastructure. This paper provides an overview of geoscience data provenance in supporting provenance-aware geoscience data and information systems by summarizing state-of-the-art technologies and methodologies of geoscience data provenance and highlighting key considerations and possible solutions for geoscience data provenance. Numéro de notice : A2013-610 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2242478 En ligne : https://doi.org/10.1109/TGRS.2013.2242478 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32746
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 11 (November 2013) . - pp 5065 - 5072[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013111 RAB Revue Centre de documentation En réserve L003 Disponible Human computation VGI provenance : Semantic web-based representation and publishing / Irene Celino in IEEE Transactions on geoscience and remote sensing, vol 51 n° 11 (November 2013)
[article]
Titre : Human computation VGI provenance : Semantic web-based representation and publishing Type de document : Article/Communication Auteurs : Irene Celino, Auteur Année de publication : 2013 Article en page(s) : pp 5137 - 5144 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] données localisées des bénévoles
[Termes IGN] qualité des données
[Termes IGN] représentation des données
[Termes IGN] service web sémantique
[Termes IGN] source de données
[Termes IGN] web 2.0
[Termes IGN] web sémantiqueRésumé : (Auteur) The collection of volunteered geographic information (VGI) is a user-generated content practice to engage a large number of citizens to collectively create geospatial data. Based on the advent of Web 2.0 and the recent increasing popularity of crowdsourcing approaches, VGI has gained the interest of the geoscience community, because of its ability to complement the collection of geographic information coming from traditional sensing technologies. However, the involvement of a crowd of volunteers, potentially untrained or nonexperts, implies that VGI can be of varying quality. Tracing VGI provenance enables the recording of the collection activity; the information about who gathered what, where and when can then be employed to judge the VGI quality. In this paper, we focus on the adoption of a provenance-based Human Computation approach to aggregate and consolidate VGI. We discuss the representation, inference and publication of Human Computation VGI and its provenance. As more and more of those community-based data collection efforts happen on the Web, we propose the adoption of Semantic Web technologies, through employing an ontological formulation to capture provenance and by following Linked Data principles to publish provenance data on the Web. Numéro de notice : A2013-614 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2252015 En ligne : https://doi.org/10.1109/TGRS.2013.2252015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32750
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 11 (November 2013) . - pp 5137 - 5144[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013111 RAB Revue Centre de documentation En réserve L003 Disponible Introducing provenance capture into a legacy data system / Helen Conover in IEEE Transactions on geoscience and remote sensing, vol 51 n° 11 (November 2013)
[article]
Titre : Introducing provenance capture into a legacy data system Type de document : Article/Communication Auteurs : Helen Conover, Auteur ; Rahul Ramachandran, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 5098 - 5104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] données localisées
[Termes IGN] droit
[Termes IGN] généalogie des données
[Termes IGN] métadonnées
[Termes IGN] norme ISO
[Termes IGN] qualité des données
[Termes IGN] source de données
[Termes IGN] traitement de données localisées
[Termes IGN] traitement interactifRésumé : (Auteur) Accurate provenance information facilitates improved understanding of Earth science data and scientific reproducibility and can serve as an indicator of data quality. Provenance capture is an integral part of many modern workflow systems but may not have been considered in the design of legacy data production systems. Furthermore, in addition to data lineage, it is also important to capture contextual information needed for understanding how a data set was produced. This paper describes our experience in retrofitting a legacy data system to support capture, storage, and dissemination of provenance. Data inputs and transformations are logged automatically, while broader context information describing science algorithms and ancillary files is manually compiled. Provenance and context information are integrated for interactive user access and embedded into data files as XML documents compliant with the “Lineage” specification for geographic metadata defined by the International Organization for Standardization in the ISO 19115-2 standard. Lessons learned from this approach can inform others who need to incorporate provenance into a data system after the fact. Numéro de notice : A2013-612 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2282817 En ligne : https://doi.org/10.1109/TGRS.2013.2282817 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32748
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 11 (November 2013) . - pp 5098 - 5104[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013111 RAB Revue Centre de documentation En réserve L003 Disponible Mapping geospatial metadata to open provenance model / Chieh-Chieh Feng in IEEE Transactions on geoscience and remote sensing, vol 51 n° 11 (November 2013)PermalinkProvenance capture and use in a satellite data processing pipeline / Scott Jensen in IEEE Transactions on geoscience and remote sensing, vol 51 n° 11 (November 2013)PermalinkLa cosmographie universelle de Guillaume le Testu (1556) : Au croisement de la géographie savante et de la science nautique des portulans / Frank Lestringant in Cartes & Géomatique, n° 216 (juin 2013)PermalinkLe portulan arabe décrit par Al-'Umari / Jean-Charles Ducène in Cartes & Géomatique, n° 216 (juin 2013)PermalinkCartographie scolaire : Simplifier sans fausser / Cécile Marin in Carto, le monde en cartes, n° 7 (septembre - octobre 2011)PermalinkDonate your geo-data! Rethinking the geo-information economy with neogeography / F. Fischer in Geoinformatics, vol 12 n° 5 (01/07/2009)PermalinkParticipation en ligne du grand public en vue de l'actualisation en continu d'une base de données / Isabelle Cléry (2008)PermalinkProduction of integrated digital terrain model from multiple datasets of different quality / T. Podobnikar in International journal of geographical information science IJGIS, vol 19 n° 1 (january 2005)Permalink