Abstract
Data preprocessing includes data cleaning, data integration, data transformation and data reduction. Data cleaning is aimed to remove unrelated or redundant items through two processes. Data integration includes three main problems and each of them can be solved by kinds of methods. Data transformation includes data generalization and property construction and standardization. Three algorithms can be used to normalize the data. The last step data reduction is used to compress the data in order to improve the quality of mining models. All these four steps are interrelated to each other and shouldn’t be separated. They work together to improve the final result of data mining.
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Zhang, W., Chen, T. (2012). Data Preprocessing for Web Data Mining. In: Jin, D., Lin, S. (eds) Advances in Electronic Commerce, Web Application and Communication. Advances in Intelligent and Soft Computing, vol 149. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28658-2_47
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DOI: https://doi.org/10.1007/978-3-642-28658-2_47
Publisher Name: Springer, Berlin, Heidelberg
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