The View Selection Problem is an optimization problem designed to enhance query performance through the pre-computation and storage of select views given resource constraints. Assuring the materialized views can be updated within a reasonable time frame has become a chief concern for recent models. However, these methods are crafted simply to fit a solution within a feasible range and not to mi...

The use of materialized views in commercial database systems and data warehousing systems is a common technique to improve the query performance. In past research, the view selection issue has essentially been investigated in the centralized context. In this paper, we address the view selection problem in a distributed scenario. We rst extend the AND-OR view graph to capture the distributed fea...

Materialized view selection is one of the most crucial techniques to design data warehouse in an optimal manner. Selecting views to materialize for the purpose of supporting the decision making efficiently is one of the most significant decisions in designing Data Warehouse. Selecting a set of derived views to materialize which minimizes the sum of total query response time and maintenance of t...

A data warehouse stores a large volume of data extracted from multiple sources. A set of materialized views is defined over the base tables in order to optimize OLAP (On-Line Analytical Processing) query response time. The selection of materialized views may be static or dynamic. The dynamic selection is continually controlled by a system that calibrates the set of views. The static selection i...

In feature selection algorithms, “stability” is the sensitivity of the chosen feature set to variations in the supplied training data. As such it can be seen as an analogous concept to the statistical variance of a predictor. However unlike variance, there is no unique definition of stability, with numerous proposed measures over 15 years of literature. In this paper, instead of defining a new ...

Three new models for the settlement selection problem are discussed and compared with the existing models. The new models determine a ranking rather than a selection, which has advantages both from the e ciency and the geographic correctness point of view. We give gures of selections based on six di erent models, and explain how the models can be implemented e ciently.

In this chapter, we revise several methods for SVM model selection, deriving from different approaches: some of them build on practical lines of reasoning but are not fully justified by a theoretical point of view; on the other hand, some methods rely on rigorous theoretical work but are of little help when applied to real–world problems, because the underlying hypotheses cannot be verified or ...