Sentence examples for spatial data warehouses from inspiring English sources

Hence, developing a Spatial OLAP (SOLAP) recommendation system would facilitate information retrieval in spatial data warehouses.

Hence, developing a SOLAP recommendation system would enhance spatial data warehouses exploitation.

Spatial data warehouses store a large amount of historized and aggregated data.

SOLAP users can exploit spatial data warehouses by launching a sequence of MDX (Multidimensional Expressions) queries.

Spatial Data warehouses (SDW) store a large amount of historized spatial data which have specific characteristics such as topology and direction.

This paper proposes a SOLAP recommendation approach that aims to help users better exploit spatial data warehouses and retrieve relevant information by recommending personalized spatial MDX (Multidimensional Expressions) queries.

The approach assists the user in spatial data warehouse exploitation through the recommendation of personalized MDX queries.

In a first phase, the current user runs a query on the spatial data warehouse stored in the Data Base Management System MySQL, through the GeoMondrian SOLAP server.

In this paper, we propose to enhance spatial data warehouse exploitation by recommending personalized MDX queries to the user taking into account his preferences and analysis needs.

A user-centered approach was taken to design a spatial data warehouse and online analytical processing (OLAP) tools for data exploration in ecological research.

Aissi et al. [14] has used ontologies for developing the SLOAP recommendation system (SLOAP) to enhance the exploration in spatial data warehouse (SLOAP) by means of querying the warehouse.