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L’impact du voisinage géographique des pays dans l’attribution des votes au Concours Eurovision de la Chanson / Jean-François Gleyze in Cybergeo, European journal of geography, n° 2011 ([01/01/2011])
[article]
Titre : L’impact du voisinage géographique des pays dans l’attribution des votes au Concours Eurovision de la Chanson Titre original : Neighbourhood impact on votes awarding in the Eurovision Song Contest Type de document : Article/Communication Auteurs : Jean-François Gleyze , Auteur Année de publication : 2011 Article en page(s) : n° 515 Note générale : bibliographie Langues : Français (fre) Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] graphe
[Termes IGN] réseau social
[Termes IGN] voisinage (relation topologique)Résumé : (auteur) The Eurovision Song Contest has been held every year since 1956. The originality of this contest lies in the points awarding system. There is no single jury but, on the contrary, each country is asked to award a given number of points to the countries which performed its favourite songs. Beyond the interest of such a system to collectively rank countries, it provides a long story of the swapped points between countries. Such information makes it possible to detect couples of countries {voter, performer} for whom votes are not exclusively guided by song quality. Currently the media covering the event regularly mention a bias in the votes distribution: according to them, this bias would be caused by geographical proximity and would lead to blocs of nearby countries which overwhelmingly vote for each other. In this article, we try to discuss this assumption. This latter requires to answer the following question: “how can we assess the influence of spatial proximity on the social ties formation?”. Besides this issue, several methodological challenges appear. First, we examine the votes of the 1993-2008 period and we identify the social ties of interest, that is the couples of countries {voter, performer} whose votes significantly diverge from the reference situation (i.e. a competition on song quality). Then, we compare the resulting social network with the spatial countries network by a well-suited statistical method to prove that “over-votes” concern nearby countries. Finally, we highlight clusters of countries tending to over-vote for each other and, in that respect, we define clustering criteria which make sense. We show that these blocs strongly structure the abnormally high votes of the 2009 event. This analysis method combines geographical and social networks and can be extended to the study of phenomena concerning relations between spatialised entities. Numéro de notice : A2011-126 Affiliation des auteurs : COGIT (1988-2011) Thématique : GEOMATIQUE Nature : Article DOI : 10.4000/cybergeo.23451 Date de publication en ligne : 10/01/2011 En ligne : https://doi.org/10.4000/cybergeo.23451 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101421
in Cybergeo, European journal of geography > n° 2011 [01/01/2011] . - n° 515[article]Relevance of airborne lidar and multispectral image data for urban scene classification using random forests / Li Guo in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 1 (January - February 2011)
[article]
Titre : Relevance of airborne lidar and multispectral image data for urban scene classification using random forests Type de document : Article/Communication Auteurs : Li Guo, Auteur ; Nesrine Chehata , Auteur ; Clément Mallet , Auteur ; Samia Boukir, Auteur Année de publication : 2011 Article en page(s) : pp 56 - 66 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse discriminante
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] écho multiple
[Termes IGN] forme d'onde pleine
[Termes IGN] image multibande
[Termes IGN] semis de points
[Termes IGN] zone urbaine denseRésumé : (Auteur) Airborne lidar systems have become a source for the acquisition of elevation data. They provide georeferenced, irregularly distributed 3D point clouds of high altimetric accuracy. Moreover, these systems can provide for a single laser pulse, multiple returns or echoes, which correspond to different illuminated objects. In addition to multi-echo laser scanners, full-waveform systems are able to record 1D signals representing a train of echoes caused by reflections at different targets. These systems provide more information about the structure and the physical characteristics of the targets. Many approaches have been developed, for urban mapping, based on aerial lidar solely or combined with multispectral image data. However, they have not assessed the importance of input features. In this paper, we focus on a multi-source framework using aerial lidar (multi-echo and full waveform) and aerial multispectral image data. We aim to study the feature relevance for dense urban scenes. The Random Forests algorithm is chosen as a classifier: it runs efficiently on large datasets, and provides measures of feature importance for each class. The margin theory is used as a confidence measure of the classifier, and to confirm the relevance of input features for urban classification. The quantitative results confirm the importance of the joint use of optical multispectral and lidar data. Moreover, the relevance of full-waveform lidar features is demonstrated for building and vegetation area discrimination. Numéro de notice : A2011-016 Affiliation des auteurs : IGN+Ext (1940-2011) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2010.08.007 Date de publication en ligne : 22/09/2010 En ligne : https://doi.org/10.1016/j.isprsjprs.2010.08.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30798
in ISPRS Journal of photogrammetry and remote sensing > vol 66 n° 1 (January - February 2011) . - pp 56 - 66[article]Réservation
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Titre : Spectral Feature Selection for Data Mining Type de document : Monographie Auteurs : Zheng Alan Zhao, Auteur ; Huan Liu, Auteur Editeur : Boca Raton, New York, ... : CRC Press Année de publication : 2011 Importance : 224 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-0-429-10719-1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse multivariée
[Termes IGN] analyse spectrale
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage semi-dirigé
[Termes IGN] corrélation à l'aide de traits caractéristiques
[Termes IGN] exploration de données
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] traitement de donnéesRésumé : (éditeur)Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified framework for supervised, unsupervised, and semisupervised feature selection.
The book explores the latest research achievements, sheds light on new research directions, and stimulates readers to make the next creative breakthroughs. It presents the intrinsic ideas behind spectral feature selection, its theoretical foundations, its connections to other algorithms, and its use in handling both large-scale data sets and small sample problems. The authors also cover feature selection and feature extraction, including basic concepts, popular existing algorithms, and applications.
A timely introduction to spectral feature selection, this book illustrates the potential of this powerful dimensionality reduction technique in high-dimensional data processing. Readers learn how to use spectral feature selection to solve challenging problems in real-life applications and discover how general feature selection and extraction are connected to spectral feature selection.Note de contenu : 1- Data of High Dimensionality and Challenges
2- Univariate Formulations for Spectral Feature Selection
3- Multivariate Formulations
4- Connections to Existing Algorithms
5- Large-Scale Spectral Feature Selection
6- Multi-Source Spectral Feature SelectionNuméro de notice : 25844 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Monographie En ligne : https://www.taylorfrancis.com/books/9780429107191 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95251 Local entropy map : a nonparametric approach to detecting spatially varying multivariate relationships / D. Guo in International journal of geographical information science IJGIS, vol 24 n° 9 (september 2010)
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Titre : Local entropy map : a nonparametric approach to detecting spatially varying multivariate relationships Type de document : Article/Communication Auteurs : D. Guo, Auteur Année de publication : 2010 Article en page(s) : pp 1367 - 1389 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse multivariée
[Termes IGN] entropie
[Termes IGN] régression linéaire
[Termes IGN] relation spatiale
[Termes IGN] variableRésumé : (Auteur) The relationship between two or more variables may change over the geographic space. The change can be in parameter values (e.g., regression coefficients) or even in relation forms (e.g., linear, quadratic, or exponential). Existing local spatial analysis methods often assume a relationship form (e.g., a linear regression model) for all regions and focus only on the change in parameter values. Therefore, they may not be able to discover local relationships of different forms simultaneously. This research proposes a nonparametric approach, a local entropy map, which does not assume a prior relationship form and can detect the existence of multivariate relationships regardless of their forms. The local entropy map calculates an approximation of the Rényi entropy for the multivariate data in each local region (in the geographic space). Each local entropy value is then converted to a p-value by comparing to a distribution of permutation entropy values for the same region. All p-values (one for each local region) are processed by several statistical tests to control the multiple-testing problem. Finally, the testing results are mapped and allow analysts to locate and interactively examine significant local relationships. The method is evaluated with a series of synthetic data sets and a real data set. Numéro de notice : A2010-406 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658811003619143 En ligne : https://doi.org/10.1080/13658811003619143 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30599
in International journal of geographical information science IJGIS > vol 24 n° 9 (september 2010) . - pp 1367 - 1389[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2010051 RAB Revue Centre de documentation En réserve L003 Disponible 079-2010052 RAB Revue Centre de documentation En réserve L003 Disponible Using clustering methods in geospatial information systems / X. Wang in Geomatica, vol 64 n° 3 (September 2010)
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Titre : Using clustering methods in geospatial information systems Type de document : Article/Communication Auteurs : X. Wang, Auteur ; Jing Wang, Auteur Année de publication : 2010 Article en page(s) : pp 347 - 361 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] analyse spatiale
[Termes IGN] attribut sémantique
[Termes IGN] distance euclidienne
[Termes IGN] exploration de données géographiques
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] regroupement de données
[Termes IGN] système d'information géographique
[Termes IGN] test de performanceRésumé : (Auteur) Spatial clustering is the process of grouping similar objects based on their distance, connectivity, or rel-ative density in space. It has been employed in the field of spatial analysis for years. In order to select the prop-er spatial clustering methods for geospatial information systems, we need to consider the characteristics of different clustering methods, relative to the objectives that we are trying to achieve. In this paper, we give a detailed discussion of different types of clustering methods from a data mining perspective. Analysis of the advantages and limitations of some classical clustering methods are given. Subsequently we discuss applying spatial clustering methods as part of geospatial information systems, with respect to distance functions, data models, non-spatial attributes and performance. Numéro de notice : A2010-529 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.5623/geomat-2010-0035 En ligne : https://doi.org/10.5623/geomat-2010-0035 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30721
in Geomatica > vol 64 n° 3 (September 2010) . - pp 347 - 361[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 035-2010031 RAB Revue Centre de documentation En réserve L003 Disponible Cartographier les pratiques et les usages des parisiens / J.L. Pinol in Le monde des cartes, n° 204 (juin 2010)PermalinkIntegrating functional diversity into tropical forest plantation designs to study ecosystem processes / Christopher Baraloto in Annals of Forest Science, vol 67 n° 3 (2010)PermalinkCommentaire de la carte des changements de l'occupation du sol dans les Rivières-du-Sud / J. Andrieu in Le monde des cartes, n° 203 (mars 2010)PermalinkExploration et représentation d'une matrice de flux / Marie Piron in Le monde des cartes, n° 203 (mars 2010)PermalinkSegmentation and reconstruction of polyhedral building roofs from aerial lidar points clouds / A. Sampath in IEEE Transactions on geoscience and remote sensing, vol 48 n° 3 Tome 2 (March 2010)PermalinkAutomatic cluster identification for environnemental applications using the self-organizing maps and a new genetic algorithm / T. Oyana in Geocarto international, vol 25 n° 1 (February 2010)PermalinkPermalinkIntégrer les coordonnées géographiques dans une analyse multivariée / Françoise de Blomac in SIG la lettre, n° 113 (janvier 2010)PermalinkNavigation Signal Processing for GNSS Software Receivers / T. Pany (2010)PermalinkUsing building permits to monitor disaster recovery: a spatio-temporal case study of coastal Mississipi following hurricane Katrina / J. Stevenson in Cartography and Geographic Information Science, vol 37 n° 1 (January 2010)Permalink