2008 · 17 citations · 22 references
ComputingInformation SystemsData EngineeringData ManagementData MiningData CleaningData PreparationData PreprocessingData QualityData WarehousingQuality Data AnalysisData Warehouse ArchitectureData Warehouse DesignMergeMerge OperationsSequential Data Preprocessing
Summary The data cleaning is the process of identifying and removing the errors in the data warehouse. Data cleaning is very important in data mining process. Most of the organizations are in the need of quality data. The quality of the data needs to be improved in the data warehouse before the mining process. The framework available for data cleaning offers the fundamental services for data cleaning such as attribute selection, formation of tokens, selection of clustering algorithm, selection of similarity function, selection of elimination function and merge function. This research paper deals about the new framework for data cleaning. It also presents a solution to handle data cleaning process by using a new framework design in a sequential order.
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Data mining: concepts and techniques
Jiawei Han, Micheline Kamber · Choice Reviews Online · 2012 · 28.9K citations
Algorithms for Mining Distance-Based Outliers in Large Datasets
Edwin M. Knorr, Raymond T. Ng · 1998 · 1.5K citations