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Data Fusion through Statistical MatchingPeter Van der PuttenLeiden University - Department of Mathematics and Computer Science Joost N. KokLeiden University - Department of Mathematics and Computer Science Amar GuptaPace University - The Seidenberg School of Computer Science and Information Systems 2002 MIT Sloan Working Paper No. 4342-02; Eller College Working Paper No. 1031-05 Abstract: In data mining applications, the availability of data is often a serious problem. For instance, elementary customer information resides in customer databases, but market survey data are only available for a subset of the customers or even for a different sample of customers. Data fusion provides a way out by combining information from different sources into a single data set for further data mining. While a significant amount of work has been done on data fusion in the past, most of the research has been performed outside of the data mining community. In this paper, we provide an overview of data fusion, introduce basic terminology and the statistical matching approach, distinguish between internal and external evaluation, and we conclude with a larger case study.
Number of Pages in PDF File: 13 Keywords: Data Mining, Data Fusion, Leveraging of Sample Data working papers seriesDate posted: February 5, 2002Suggested CitationContact Information
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