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Popularity-aware collective keyword queries in road networks / Sen Zhao in Geoinformatica, vol 21 n° 3 (July - September 2017)
[article]
Titre : Popularity-aware collective keyword queries in road networks Type de document : Article/Communication Auteurs : Sen Zhao, Auteur ; Xiang Cheng, Auteur ; Sen Su, Auteur ; Kai Shuang, Auteur Année de publication : 2017 Article en page(s) : pp 485 - 518 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] graphe
[Termes IGN] langage de requête
[Termes IGN] langage naturel (informatique)
[Termes IGN] point d'intérêt
[Termes IGN] positionnement automatique
[Termes IGN] requête (informatique)
[Termes IGN] réseau routierRésumé : (Auteur) This paper addresses a popularity-aware collective keyword (PAC-K) query in road networks. Given a road network with POIs (Points of Interest), which is modeled as a road network graph, where each node locating in a two-dimensional space represents a road intersection or a POI, and each edge with weight represents a road segment, the PACK query aims to find a group of popular POIs (i.e., a popular region) that cover the query’s keywords and satisfy the distance requirements from each node to the query node and between each pair of nodes, such that the sum of rating scores over these nodes for the query keywords is maximized. We show the problem of answering the PACK query is NP-Hard. To solve this problem, we present exact and heuristic solutions on small and large road networks, respectively. In particular, to improve query performance, we propose a rating score scaling technique to reduce the search space and a redundant computation reducing technique to reduce the excessive redundant computations in query processing. Extensive performance studies using two real datasets confirm the efficiency, accuracy, and scalability of the proposed solutions. Numéro de notice : A2017-378 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-017-0299-9 En ligne : https://doi.org/10.1007/s10707-017-0299-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85810
in Geoinformatica > vol 21 n° 3 (July - September 2017) . - pp 485 - 518[article]Automatic targeted-domain spatiotemporal event detection in twitter / Ting Hua in Geoinformatica, vol 20 n° 4 (October - December 2016)
[article]
Titre : Automatic targeted-domain spatiotemporal event detection in twitter Type de document : Article/Communication Auteurs : Ting Hua, Auteur ; Feng Chen, Auteur ; Liang Zhao, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 765 - 795 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse spatio-temporelle
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] positionnement automatique
[Termes IGN] TwitterRésumé : (Auteur) Twitter has become an important data source for detecting events, especially tracking detailed information for events of a specific domain. Previous studies on targeted-domain Twitter information extraction have used supervised learning techniques to identify domain-related tweets, however, the need for extensive manual labeling makes these supervised systems extremely expensive to build and maintain. What’s more, most of these existing work fail to consider spatiotemporal factors, which are essential attributes of target-domain events. In this paper, we propose a semi-supervised method for Automatical Targeted-domain Spatiotemporal Event Detection (ATSED) in Twitter. Given a targeted domain, ATSED first learns tweet labels from historical data, and then detects on-going events from real-time Twitter data streams. Specifically, an efficient label generation algorithm is proposed to automatically recognize tweet labels from domain-related news articles, a customized classifier is created for Twitter data analysis by utilizing tweets’ distinguishing features, and a novel multinomial spatial-scan model is provided to identify geographical locations for detected events. Experiments on 305 million tweets demonstrated the effectiveness of this new approach. Numéro de notice : A2016-815 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article DOI : 10.1007/s10707-016-0263-0 En ligne : http://dx.doi.org/10.1007/s10707-016-0263-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82616
in Geoinformatica > vol 20 n° 4 (October - December 2016) . - pp 765 - 795[article]Discovery of local topics by using latent spatio-temporal relationships in geo-social media / Kyoung-Sook Kim in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
[article]
Titre : Discovery of local topics by using latent spatio-temporal relationships in geo-social media Type de document : Article/Communication Auteurs : Kyoung-Sook Kim, Auteur ; Isao Kojima, Auteur ; Hirotaka Ogawa, Auteur Année de publication : 2016 Article en page(s) : pp 1899 - 1922 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données massives
[Termes IGN] données spatiotemporelles
[Termes IGN] géovisualisation
[Termes IGN] positionnement automatique
[Termes IGN] temps réel
[Termes IGN] traitement de donnéesRésumé : (Auteur) Social networks have played a crucial role as information channels for people to understanding their daily lives beyond merely being communication tools. In particular, coupling social networks with geographic location has boosted the worth of social media to not only enable comprehension of the effects of natural phenomena such as global warming and disasters, but also the social patterns of human societies. However, the high rate of social data generation and the large amounts of noisy data makes it difficult to directly apply social media to decision-making processes. This article proposes a new system of analyzing the spatio-temporal patterns of social phenomena in real time and the discovery of local topics based on their latent spatio-temporal relationships. We will first describe a model that represents the local patterns of populations of geo-tagged social media. We will then define a local topic whose keywords share a region in space and time and present a system implementation based on existing open source technologies. We evaluated the model of local topics with several ways of visualization in experiments and demonstrated a certain social pattern from a dataset of daily Twitter streams. The results obtained from experiments revealed certain keywords had a strong spatio-temporal proximity even though they did not occur in the same message. Numéro de notice : A2016-571 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1146956 En ligne : http://dx.doi.org/10.1080/13658816.2016.1146956 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81715
in International journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 1899 - 1922[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Enabling maps/location searches on mobile devices: constructing a POI database via focused crawling and information extraction / Hsiu-Min Chuang in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)
[article]
Titre : Enabling maps/location searches on mobile devices: constructing a POI database via focused crawling and information extraction Type de document : Article/Communication Auteurs : Hsiu-Min Chuang, Auteur ; Chia-Hui Chang, Auteur ; Ting-Yao Kao, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1405 - 1425 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] exploration de données
[Termes IGN] extraction de données
[Termes IGN] point d'intérêt
[Termes IGN] positionnement automatique
[Termes IGN] recherche d'information
[Termes IGN] service fondé sur la position
[Termes IGN] téléphonie mobileRésumé : (Auteur) With the popularity of mobile devices and smartphones, we have witnessed rapid growth in mobile applications and services, especially in location-based services (LBS). According to a mobile marketing survey, maps/location searches are among the most utilized services on smartphones. Points of interest (POIs), such as stores, shops, gas stations, parking lots, and bus stops, are particularly important for maps/location searches. Existing map services such as Google Maps and Wikimapia are constructed manually either professionally or with crowd sourcing. However, manual annotation is costly and limited in current POI search services. With the abundance of information on the Web, many store POIs can be extracted from the Web. In this paper, we focus on automatically constructing a POI database to enable store POI map searches. We propose techniques that are required to construct a POI database, including focused crawling, information extraction, and information retrieval techniques. We first crawl Yellow Page web sites to obtain vocabularies of store names. These vocabularies are then investigated with search engines to obtain sentences containing these store names from search snippets in order to train a store name recognition model. To extract POIs scattered across the Web, we propose a query-based crawler to find address-bearing pages that might be used to extract addresses and store names. We crawled 1.25 million distinct POI pairs scattered across the Web and implemented a POI search service via Apache Lucent’s search platform, called Solr. The experimental results demonstrate that the proposed geographical information retrieval model outperforms Wikimapia and a commercial app called ‘What’s the Number?’ Numéro de notice : A2016-309 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1133820 En ligne : http://dx.doi.org/10.1080/13658816.2015.1133820 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80909
in International journal of geographical information science IJGIS > vol 30 n° 7- 8 (July - August 2016) . - pp 1405 - 1425[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016042 RAB Revue Centre de documentation En réserve L003 Disponible 079-2016041 RAB Revue Centre de documentation En réserve L003 Disponible Estimating attendance from cellular network data / Marco Marmei in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)
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Titre : Estimating attendance from cellular network data Type de document : Article/Communication Auteurs : Marco Marmei, Auteur ; Massimo Colonna, Auteur Année de publication : 2016 Article en page(s) : pp 1281 - 1301 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique
[Termes IGN] acquisition de données
[Termes IGN] approche participative
[Termes IGN] données localisées des bénévoles
[Termes IGN] positionnement automatique
[Termes IGN] téléphonie mobileRésumé : (Auteur) An automatic estimate of the number of attendees to events happening in the city can provide valuable information to geographic information systems and geo-located applications. We present a methodology to estimate the number of events’ attendees from cellular network data. In this work, we used anonymized Call Detail Records (CDRs) comprising data on where and when users access the cellular network. Our approach is based on two key ideas: (1) we identify the network cells associated with the event location. (2) We verify the attendance of each user, as a measure of whether (s)he generates CDRs during the event, but not during other times. We evaluate our approach to estimate the number of attendees to a number of events ranging from football matches in stadiums to concerts and festivals in open squares. Comparing our results with the best groundtruth data available, our estimates provide a median error of less than 15% of the actual number of attendees. Numéro de notice : A2016-306 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1127378 En ligne : http://dx.doi.org/10.1080/13658816.2015.1127378 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80905
in International journal of geographical information science IJGIS > vol 30 n° 7- 8 (July - August 2016) . - pp 1281 - 1301[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016042 RAB Revue Centre de documentation En réserve L003 Disponible 079-2016041 RAB Revue Centre de documentation En réserve L003 Disponible 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)PermalinkSpatio-temporal traffic video data archiving and retrieval system / Hang Yue in Geoinformatica, vol 20 n° 1 (January - March 2016)PermalinkSee where we’re up to / Sarah Durante in GEO: Geoconnexion international, vol 14 n° 10 (November 2015)PermalinkRecommendations in location-based social networks: a survey / Jie Bao in Geoinformatica, vol 19 n° 3 (July - September 2015)PermalinkIntegrative representation and inference of qualitative locations about points, lines, and polygons / Shihong Du in International journal of geographical information science IJGIS, vol 29 n° 6 (June 2015)PermalinkLocating control points in aerial images with a multi-scale approach based on terrestrial image patches / Adilson Berveglieri in Photogrammetric record, vol 30 n° 149 (March - May 2015)PermalinkLiDAR strip adjustment using multifeatures matched with aerial images / Yongjun Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)PermalinkL’institut national de l’information géographique et forestière / Institut national de l'information géographique et forestière (2012 -) (2015)PermalinkFour theses / Ulf Almroth (1991)Permalink