Attribute generalization depends on the following rule: If there is a huge collection of distinct values for an attribute in the original working relation, and there exists a group of generalization operators on the attribute, thus a generalization operator should be choose and utilized to the attribute.This rule depends on ... Read More

AOI stands for Attribute-Oriented Induction. The attribute-oriented induction approach to concept description was first proposed in 1989, a few years before the introduction of the data cube approach. The data cube approach is essentially based on materialized views of the data, which typically have been pre-computed in a data warehouse.In ... Read More

Data generalization summarizes data by replacing relatively low-level values (such as numeric values for an attribute age) with higher-level concepts (such as young, middleaged, and senior). Given the high amount of data saved in databases, it is beneficial to be able to define concepts in concise and succinct terms at ... Read More

The curse of dimensionality and the need for understandable results pose serious challenges for finding an efficient and scalable solution to the cubegrade problem. It can be confined but interesting version of the cubegrade problem, called constrained multidimensional gradient analysis. It can reduces the search space and derives interesting results.There ... Read More

There are three measures are used as exception indicators to support recognize data anomalies. These measures denotes the degree of surprise that the quantity in a cell influence, concerning its expected value.The measures are computed and associated with every cell, for all levels of aggregation. They are as follows including ... Read More

Discovery-driven exploration is such a cube exploration approach. In discovery-driven exploration, precomputed measures indicating data exceptions are used to guide the user in the data analysis process, at all levels of aggregation. It refer to these measures as exception indicators.Intuitively, an exception is a data cube cell value that is ... Read More

Data Warehousing is an approach that can collect and handle data from multiple sources to provide the business a significant business insight. A data warehouse is specifically created for the goals of support management decisions.In simple terms, a data warehouse defines a database that is maintained independently from an organization’s ... Read More

Measures can be organized into three elements including distributive, algebraic, and holistic. It depends on the type of aggregate functions used.Distributive − An aggregate function is distributive if it can be calculated in a delivered manner as follows. Consider the data are independent into n sets. It can use the ... Read More

Entropy-based discretization is a supervised, top-down splitting approach. It explores class distribution data in its computation and preservation of split-points (data values for separation an attribute range). It can discretize a statistical attribute, A, the method choose the value of A that has the minimum entropy as a split-point, and ... Read More

The utility lies in the fact that the wavelet transformed data can be limited. A compressed approximation of the information can be retained by saving only a small fraction of the principal of the wavelet coefficients. For instance, all wavelet coefficients higher than some user-defined threshold can be maintained. Some ... Read More