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Querying visible points in large obstructed space / Jianqiu Xu in Geoinformatica, vol 19 n° 3 (July - September 2015)  

Public [article]  inGeoinformatica > vol 19 n° 3 (July - September 2015) . - pp 435 - 461 Titre : Querying visible points in large obstructed space Type de document : Article/Communication Auteurs : Jianqiu Xu, Auteur ; Ralf Hartmut Güting, Auteur Année de publication : 2015 Article en page(s) : pp 435 - 461 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] base de données localisées [Termes IGN] géomètrie algorithmique [Termes IGN] noeud [Termes IGN] performance [Termes IGN] point d'intérêt [Termes IGN] structure de données localisées [Termes IGN] traitement automatique de données [Termes IGN] traitement de données localisées [Termes IGN] triangulation (topologie) Résumé : (auteur) Querying visible points is a fundamental problem in computational geometry and spatial databases. With the development of new applications such as trip planning and nearest neighbors, querying visible points plays a key role in obstacle space and the result can be further used such as defining the shortest path. Thereby, efficiently finding the result is essentially important. However, the performance of current methods decrease substantially for large datasets. To solve the problem, we proposes a new and fast algorithm to find visible points for an arbitrary query location inside a large polygon containing obstacles. The method is based on polygon triangulation. By decomposing the polygon into a set of triangles, we manage the polygon by organizing triangles in an efficient way instead of maintaining a large number of vertices. We propose a data structure to partition the searching space into several parts, each of which is independently processed. Afterwards, by recursively calling a method we search visible points by accessing triangles and return the result in a progressive way. Through a theoretical analysis, assuming the polygon contains N vertices in total, the time complexity of our algorithm is O(N), improving the existing method O(N l o g N). We prove the correctness of the algorithm and analyze the space complexity, which is O(N). The technique is extended to return visible points less than a threshold distance to the query location. Using both synthetic and real datasets, we perform extensive experiments to test our algorithm and demonstrate its efficiency and effectiveness. Visible points are efficiently processed in a large obstacle space with over one million vertices. Experimental results show that our technique gains more than one order of magnitude speedup compared to competitive methods using large datasets. Numéro de notice : A2015-495 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-014-0213-7 Date de publication en ligne : 15/08/2014 En ligne : https://doi.org/10.1007/s10707-014-0213-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77307 [article]

The TM-RTree: an index on generic moving objects for range queries / Jianqiu Xu in Geoinformatica, vol 19 n° 3 (July - September 2015)  

Public [article]  inGeoinformatica > vol 19 n° 3 (July - September 2015) . - pp 487 - 524 Titre : The TM-RTree: an index on generic moving objects for range queries Type de document : Article/Communication Auteurs : Jianqiu Xu, Auteur ; Ralf Hartmut Güting, Auteur ; Yu Zheng, Auteur Année de publication : 2015 Article en page(s) : pp 487 - 524 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] arbre-R [Termes IGN] distance [Termes IGN] données spatiotemporelles [Termes IGN] index spatial [Termes IGN] objet mobile [Termes IGN] requête spatiale [Termes IGN] transport Résumé : (auteur) Existing works on moving objects mainly focus on a single environment such as free space and road network, and do not investigate the complete trip for humans who can pass several environments, e.g., road network, pavement areas, indoor. In this paper, we consider multiple environments and study moving objects with different transportation modes, also called generic moving objects. We aim to answer a new class of queries supporting three kinds of conditions: temporal, spatial, and transportation modes. To efficiently provide the result, we propose an index structure called TM-RTree, which takes into account the feature of moving objects in different environments and has the capability of managing objects on not only temporal and spatial data but also transportation modes. This property is not maintained by existing indices for moving objects. Different cases on transportation modes are supported. Correspondingly, several algorithms are developed. The TM-RTree and related algorithms are developed in a real DBMS to have a practical and solid result for applications. In the experiment, we conduct the performance evaluation using extensive datasets and compare the proposed technique with the other two competitors, demonstrating the efficiency and significant superiority of our solution in various settings. Numéro de notice : A2015-496 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-014-0218-2 Date de publication en ligne : 11/09/2014 En ligne : https://doi.org/10.1007/s10707-014-0218-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77308 [article]

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]

A comparison and evaluation of map construction algorithms using vehicle tracking data / Mahmuda Ahmed in Geoinformatica, vol 19 n° 3 (July - September 2015)  

Public [article]  inGeoinformatica > vol 19 n° 3 (July - September 2015) . - pp 601 - 632 Titre : A comparison and evaluation of map construction algorithms using vehicle tracking data Type de document : Article/Communication Auteurs : Mahmuda Ahmed, Auteur ; Sophia Karagiorgou, Auteur ; Dieter Pfose, Auteur ; Carola Wenk, Auteur Année de publication : 2015 Article en page(s) : pp 601 - 632 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse comparative [Termes IGN] cartographie automatique [Termes IGN] conception cartographique [Termes IGN] évaluation [Termes IGN] lever mobile [Termes IGN] test de performance Résumé : (auteur) Map construction methods automatically produce and/or update street map datasets using vehicle tracking data. Enabled by the ubiquitous generation of geo-referenced tracking data, there has been a recent surge in map construction algorithms coming from different computer science domains. A cross-comparison of the various algorithms is still very rare, since (i) algorithms and constructed maps are generally not publicly available and (ii) there is no standard approach to assess the result quality, given the lack of benchmark data and quantitative evaluation methods. This work represents a first comprehensive attempt to benchmark such map construction algorithms. We provide an evaluation and comparison of seven algorithms using four datasets and four different evaluation measures. In addition to this comprehensive comparison, we make our datasets, source code of map construction algorithms and evaluation measures publicly available on http://​mapconstruction.​org.​ This site has been established as a repository for map construction data and algorithms and we invite other researchers to contribute by uploading code and benchmark data supporting their contributions to map construction algorithms. Numéro de notice : A2015-498 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-014-0222-6 Date de publication en ligne : 28/10/2014 En ligne : https://doi.org/10.1007/s10707-014-0222-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77310 [article]