data processing

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Related to Data preprocessing: data mining

data processing

the organization and processing of information in a business. The use of COMPUTERS to store data (see DATA STORAGE) and to undertake routine data processing activities such as recording purchases, sales, payroll etc. can save time, improve recording accuracy and reduce staffing costs. See INFORMATION MANAGEMENT, LOCAL AREA NETWORK.
References in periodicals archive ?
The architecture involves the following phases data preprocessing, quantifier and input slicer and hadoop framework and the analytical engine.
And then a solution method under the large data environment is proposed: Firstly, the matrix vector is used to improve the FCM clustering, in order to make it conform to the processing of the data and get the whole power load curve of the study area after data preprocessing.
In this paper, to enhance the forecasting capacity of the proposed combined model, consisting of three procedures, the data preprocessing procedure, the artificial intelligent parameter optimization introduction procedure, and the parameter optimization approach modification procedure were integrated.
Data preprocessing evaluation for web log mining: Reconstruction of activities of a web visitor.
In general, building a classifier need two steps, including data preprocessing and selecting a proper classification algorithm to train the classification model using a dataset got by preprocessing.
The steps needed for data preprocessing were presented in detail in (Dinuca, 2011).
3) proposes a series of steps for data preprocessing for web usage mining.
Grocers need a software solution that considers all safes step-by-step and cost-relevant factors in the data preprocessing, forecast calculation, demand calculation and order optimization.
It consists of five related phases, which are the data acquisition, visualization, data preprocessing, the reference model construction and the application of landmark placement.
Topics include a means for comprehensive analysis of the effect of microarray data preprocessing methods on differentially expressed transcript selection, differentiation detection in microarray normalization, spatial de-trending and normalization methods for two-channel DNA and protein microarray data, a survey of cDNA microarray normalization, technical variations in modeling the joint expression of several genes, analysis for certain data normalization, and array-based analysis for the detection of chromosomal aberrations and copy number variations.
Section III covers methods of data preprocessing and results interpretation.