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An interactive framework for spatial joins : a statistical approach to data analysis in GIS / S. Alkobaisi in Geoinformatica, vol 16 n° 2 (April 2012)  

Public [article]  inGeoinformatica > vol 16 n° 2 (April 2012) . - pp 329 - 355 Titre : An interactive framework for spatial joins : a statistical approach to data analysis in GIS Type de document : Article/Communication Auteurs : S. Alkobaisi, Auteur ; W. Bae, Auteur ; P. Vojtechovsky, Auteur ; S. Narayanappa, Auteur Année de publication : 2012 Article en page(s) : pp 329 - 355 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de données [Termes IGN] arbre quadratique [Termes IGN] arbre-R [Termes IGN] système d'information géographique Résumé : (Auteur) Many Geographic Information Systems (GIS) handle a large volume of geospatial data. Spatial joins over two or more geospatial datasets are very common operations in GIS for data analysis and decision support. However, evaluating spatial joins can be very time intensive due to the size of datasets. In this paper, we propose an interactive framework that provides faster approximate answers of spatial joins. The proposed framework utilizes two statistical methods: probabilistic join and sampling based join. The probabilistic join method provides speedup of two orders of magnitude with no correctness guarantee, while the sampling based method provides an order of magnitude improvement over the full indexing tree joins of datasets and also provides running confidence intervals. The framework allows users to trade-off speed versus bounded accuracy, hence it provides truly interactive data exploration. The two methods are evaluated empirically with real and synthetic datasets. Numéro de notice : A2012-090 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-011-0134-7 Date de publication en ligne : 19/08/2011 En ligne : https://doi.org/10.1007/s10707-011-0134-719/08/2011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31538 [article]

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IRSJ : incremental refining spatial joins for interactive queries in GIS / W. Bae in Geoinformatica, vol 14 n° 4 (October 2010)  

Public [article]  inGeoinformatica > vol 14 n° 4 (October 2010) . - pp 507 - 543 Titre : IRSJ : incremental refining spatial joins for interactive queries in GIS Type de document : Article/Communication Auteurs : W. Bae, Auteur ; S. Leuttenegger, Auteur ; S. Alkobaisi, Auteur Année de publication : 2010 Article en page(s) : pp 507 - 543 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] base de données relationnelles [Termes IGN] interactivité [Termes IGN] jeu de données localisées [Termes IGN] jointure spatiale [Termes IGN] requête spatiale [Termes IGN] système d'information géographique Résumé : (Auteur) An increasing number of emerging web database applications deal with large georeferenced data sets. However, exploring these large data sets through spatial queries can be very time and resource intensive. The need for interactive spatial queries has arisen in many applications such as Geographic Information Systems (GIS) for efficient decision-support. In this paper, we propose a new interactive spatial query processing technique for GIS. We present a family of the Incremental Refining Spatial Join (IRSJ) algorithms that can be used to report incrementally refined running estimates for aggregate queries while simultaneously displaying the actual query result tuples of the data sets sampled so far. Our goal is to minimize the time until an acceptably accurate estimate of the query result is available (to users) measured by a confidence interval. Our approach enables more interactive data exploration and analysis. While similar work has been done in relational databases, to the best of our knowledge, this is the first work using this approach in GIS. We investigate and evaluate different sampling methodologies through extensive experimental performance comparisons. Experiments on both real and synthetic data show an order of magnitude response time improvement relative to the final answer obtained when using a full R-tree join. We also show the impact of different index structures on the performance of our algorithms using three known sampling methods. Numéro de notice : A2010-306 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s10707-009-0089-0 Date de publication en ligne : 08/08/2009 En ligne : https://doi.org/10.1007/s10707-009-0089-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30500 [article]

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Web data retrieval: solving spatial range queries using k-nearest neighbor searches / W. Bae in Geoinformatica, vol 13 n° 4 (December 2009)  

Public [article]  inGeoinformatica > vol 13 n° 4 (December 2009) . - pp 483 - 514 Titre : Web data retrieval: solving spatial range queries using k-nearest neighbor searches Type de document : Article/Communication Auteurs : W. Bae, Auteur ; S.H. Kim, Auteur ; S. Alkobaisi, Auteur ; et al., Auteur Année de publication : 2009 Article en page(s) : pp 483 - 514 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] classification barycentrique [Termes IGN] géomatique web [Termes IGN] interface web [Termes IGN] recherche d'information géographique [Termes IGN] requête spatiale [Termes IGN] système d'information géographique Résumé : (Auteur) As Geographic Information Systems (GIS) technologies have evolved, more and more GIS applications and geospatial data are available on the web. Spatial objects in a given query range can be retrieved using spatial range query - one of the most widely used query types in GIS and spatial databases. However, it can be challenging to retrieve these data from various web applications where access to the data is only possible through restrictive web interfaces that support certain types of queries. A typical scenario is the existence of numerous business web sites that provide their branch locations through a limited “nearest location” web interface. For example, a chain restaurant’s web site such as McDonalds can be queried to find some of the closest locations of its branches to the user’s home address. However, even though the site has the location data of all restaurants in, for example, the state of California, it is difficult to retrieve the entire data set efficiently due to its restrictive web interface. Considering that k-Nearest Neighbor (k-NN) search is one of the most popular web interfaces in accessing spatial data on the web, this paper investigates the problem of retrieving geospatial data from the web for a given spatial range query using only k-NN searches. Based on the classification of k-NN interfaces on the web, we propose a set of range query algorithms to completely cover the rectangular shape of the query range (completeness) while minimizing the number of k-NN searches as possible (efficiency). We evaluated the efficiency of the proposed algorithms through statistical analysis and empirical experiments using both synthetic and real data sets. Copyright Springer Numéro de notice : A2009-336 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-008-0055-2 En ligne : https://doi.org/10.1007/s10707-008-0055-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29966 [article]

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