Todo DSpace
Listar por tema "Spatial queries"

Mostrando ítems 1-10 de 10

    • Bulk insertions into xBR+-trees 

      Roumelis G., Vassilakopoulos M., Corral A., Manolopoulos Y. (2017)
      Bulk insertion refers to the process of updating an existing index by inserting a large batch of new data, treating the items of this batch as a whole and not by inserting these items one-by-one. Bulk insertion is related ...

    • Efficient distance join query processing in distributed spatial data management systems 

      García-García F., Corral A., Iribarne L., Vassilakopoulos M., Manolopoulos Y. (2020)
      Due to the ubiquitous use of spatial data applications and the large amounts of such data these applications use, the processing of large-scale distance joins in distributed systems is becoming increasingly popular. Distance ...

    • An efficient flash-aware spatial index for points 

      Carniel A.C., Roumelis G., Ciferri R.R., Vassilakopoulos M., Corral A., Ciferri C.D.deA. (2018)
      Spatial database systems often employ spatial indices to speed up the processing of spatial queries. In addition, modern spatial database applications are interested in exploiting the positive characteristics of flash-based ...

    • Efficient large-scale distance-based join queries in spatialhadoop 

      García-García F., Corral A., Iribarne L., Vassilakopoulos M., Manolopoulos Y. (2018)
      Efficient processing of Distance-Based Join Queries (DBJQs) in spatial databases is of paramount importance in many application domains. The most representative and known DBJQs are the K Closest Pairs Query (KCPQ) and the ...

    • An Improved GPU-based Algorithmfor Processing the k Nearest Neighbor Query 

      Velentzas P., Moutafis P., Mavrommatis G. (2020)
      The k Nearest Neighbor (k-NN) query is a common spatial query that appears in several big data applications. We propose and implement a new GPU-based algorithm for the k-NN query, which improves our previous Symmetric ...

    • Improving Distance-Join Query processing with Voronoi-Diagram based partitioning in SpatialHadoop 

      García-García F., Corral A., Iribarne L., Vassilakopoulos M. (2020)
      SpatialHadoop is an extended MapReduce framework supporting global indexing techniques that partition spatial datasets across several machines and improve spatial query processing performance compared to traditional Hadoop ...

    • Nearest Neighbor Algorithms using xBR-Trees 

      Roumelis, G.; Vassilakopoulos, M.; Corral, A. (2011)
      One of the common queries in spatial databases is the (K) Nearest Neighbor Query that discovers the (K) closest objects to a query object. Processing of spatial queries, in most cases, is accomplished by indexing spatial ...

    • New plane-sweep algorithms for distance-based join queries in spatial databases 

      Roumelis G., Corral A., Vassilakopoulos M., Manolopoulos Y. (2016)
      Efficient and effective processing of the distance-based join query (DJQ) is of great importance in spatial databases due to the wide area of applications that may address such queries (mapping, urban planning, transportation ...

    • A Partitioning GPU-based Algorithm for Processing the k Nearest-Neighbor Query 

      Velentzas P., Vassilakopoulos M., Corral A. (2020)
      The k Nearest-Neighbor (k-NN) query is a common spatial query that appears in several big data applications. Typically, GPU devices have much larger numbers of processing cores than CPUs and faster device memory than main ...

    • Prepartitioning in MapReduce Processing of Group Nearest-Neighbor Query 

      Moutafis P., Mavrommatis G., Velentzas P. (2020)
      Given two datasets of points (called Query and Training), the Group (K) Nearest-Neighbor (GKNN) query retrieves (K) points of the Training with the smallest sum of distances to every point of the Query. This spatial query ...