Abstract

http://ssrn.com/abstract=297501
 
 

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Data Fusion through Statistical Matching


Peter Van der Putten


Leiden University - Department of Mathematics and Computer Science

Joost N. Kok


Leiden University - Department of Mathematics and Computer Science

Amar Gupta


Pace 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

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Date posted: February 5, 2002  

Suggested Citation

van der Putten, Peter and Kok, Joost N. and Gupta, Amar, Data Fusion through Statistical Matching (2002). MIT Sloan Working Paper No. 4342-02; Eller College Working Paper No. 1031-05. Available at SSRN: http://ssrn.com/abstract=297501 or http://dx.doi.org/10.2139/ssrn.297501

Contact Information

Peter Van der Putten
Leiden University - Department of Mathematics and Computer Science ( email )
Niels Bohrweg 1
2333 CA Leiden
Netherlands
Joost N. Kok
Leiden University - Department of Mathematics and Computer Science ( email )
Niels Bohrweg 1
2333 CA Leiden
Netherlands
Amar Gupta (Contact Author)
Pace University - The Seidenberg School of Computer Science and Information Systems ( email )
163 William Street
New York, NY 10038
United States
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