Sentence examples for multidimensional data sources from inspiring English sources

The idea of using preWeight is to adjust for prior information/evidence imbalance across multidimensional data sources.

Additionally, as a large volume of electronic medical records (EMRs) and FDA drug labels become available and effective text mining approaches were developed [ 29], the development of the novel methods to integrate multidimensional data sources and build a comprehensive resource for adverse drug interactions will be possible and practical.

The main problem is that we lose the relationships between requirements, elements in the multidimensional (MD) conceptual models and data sources in the process, since no traceability is explicitly specified.

Except for the work of Bargui et al. [5] which uses linguistic relationships, existing mixed methods rely on an exact match between the names of the multidimensional schema and data source schema elements; such assumption is too restrictive given the domains differences (decision making and information system).

ITK is an open-source software used for registering multidimensional data [2].

Thus, we propose a hybrid approach to develop DWs, i.e., we firstly obtain the conceptual multidimensional model of the DW from user requirements and then we verify and enforce its correctness against data sources by using a set of QVT relations based on multidimensional normal forms.

Then, we make use of the multidimensional normal forms to define a set of Query/View/Transformation (QVT) relations to assure that the conceptual multidimensional model obtained from user requirements agrees with the available data sources that will populate the DW.

Our approach includes a set of traces and their formalization, in order to relate the multidimensional elements specified by user requirements with the concepts extracted from data sources.

Existing EISs commonly adopt data warehousing technology to consolidate data from multiple sources in a tailor-made fashion, and support predefined multidimensional data analysis.

Thus, the resulting multidimensional schema would satisfy the end-user requirements and would be conciliated with the data sources.

This project involved indexing multidimensional data for near-neighbor searches.