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Recommendations in location-based social networks: a survey / Jie Bao in Geoinformatica, vol 19 n° 3 (July - September 2015)  

Public [article]  inGeoinformatica > vol 19 n° 3 (July - September 2015) . - pp 525 - 565 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] utilisateur Résumé : (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 [article]

Query-aware location anonymization for road networks / C. Chow in Geoinformatica, vol 15 n° 3 (July 2011)  

Public [article]  inGeoinformatica > vol 15 n° 3 (July 2011) . - pp 571 - 607 Titre : Query-aware location anonymization for road networks Type de document : Article/Communication Auteurs : C. Chow, Auteur ; M. Mokbel, Auteur ; Jie Bao, Auteur ; X. Liu, Auteur Année de publication : 2011 Article en page(s) : pp 571 - 607 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] espace euclidien [Termes IGN] requête spatiale [Termes IGN] réseau routier [Termes IGN] service fondé sur la position Résumé : (Auteur) Recently, several techniques have been proposed to protect the user location privacy for location-based services in the Euclidean space. Applying these techniques directly to the road network environment would lead to privacy leakage and inefficient query processing. In this paper, we propose a new location anonymization algorithm that is designed specifically for the road network environment. Our algorithm relies on the commonly used concept of spatial cloaking, where a user location is cloaked into a set of connected road segments of a minimum total length L including at least K users. Our algorithm is “query-aware” as it takes into account the query execution cost at a database server and the query quality, i.e., the number of objects returned to users by the database server, during the location anonymization process. In particular, we develop a new cost function that balances between the query execution cost and the query quality. Then, we introduce two versions of our algorithm, namely, pure greedy and randomized greedy, that aim to minimize the developed cost function and satisfy the user specified privacy requirements. To accommodate intervals with a high workload, we introduce a shared execution paradigm that boosts the scalability of our location anonymization algorithm and the database server to support large numbers of queries received in a short time period. Extensive experimental results show that our algorithms are more efficient and scalable than the state-of-the-art technique, in terms of both query execution cost and query quality. The results also show that our algorithms have very strong resilience to two privacy attacks, namely, the replay attack and the center-of-cloaked-area attack. Numéro de notice : A2011-212 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-010-0117-0 Date de publication en ligne : 06/11/2010 En ligne : https://doi.org/10.1007/s10707-010-0117-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30990 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
057-2011031	RAB	Revue	Centre de documentation	En réserve L003	Disponible