Wrapper / Monitor Wrapper / Monitor Wrapper / Monitor
نویسنده
چکیده
The topic of data warehousing encompasses architec-tures, algorithms, and tools for bringing together selected data from multiple databases or other information sources into a single repository, called a data warehouse , suitable for direct querying or analysis. In recent years data warehousing has become a prominent buz-zword in the database industry, but attention from the database research community has been limited. In this paper we motivate the concept of a data warehouse, we outline a general data warehousing architecture, and we propose a number of technical issues arising from the architecture that we believe are suitable topics for exploratory research.
منابع مشابه
Modularized design for wrappers/monitors in data warehouse systems
To simplify the task of constructing wrapper/monitor for the information sources in data warehouse systems, we provide a modularized design method to re-use the code. By substituting some parts of wrapper modules, we can re-use the wrapper on a dierent information source. For each information source, we also develop a toolkit to generate a corresponding monitor. By the method, we can reduce mu...
متن کاملA Hybrid Approach for Biomarker Discovery from Microarray Gene Expression Data for Cancer Classification
Microarrays allow researchers to monitor the gene expression patterns for tens of thousands of genes across a wide range of cellular responses, phenotype and conditions. Selecting a small subset of discriminate genes from thousands of genes is important for accurate classification of diseases and phenotypes. Many methods have been proposed to find subsets of genes with maximum relevance and min...
متن کاملDeveloping a Filter-Wrapper Feature Selection Method and its Application in Dimension Reduction of Gen Expression
Nowadays, increasing the volume of data and the number of attributes in the dataset has reduced the accuracy of the learning algorithm and the computational complexity. A dimensionality reduction method is a feature selection method, which is done through filtering and wrapping. The wrapper methods are more accurate than filter ones but perform faster and have a less computational burden. With ...
متن کاملLearning with Local Drift Detection
Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem of learning when the distribution that generates the examples changes over time. We present a method for detection of changes in the probability distribution of examples. The idea behind the drift detection method is to monito...
متن کاملFuzzy-rough Information Gain Ratio Approach to Filter-wrapper Feature Selection
Feature selection for various applications has been carried out for many years in many different research areas. However, there is a trade-off between finding feature subsets with minimum length and increasing the classification accuracy. In this paper, a filter-wrapper feature selection approach based on fuzzy-rough gain ratio is proposed to tackle this problem. As a search strategy, a modifie...
متن کامل