Data fusion through statistical matching
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Author
Contributions
- Kok, Joost N. - Contributor
- Gupta, Amar. - Contributor
- Sloan School of Management. - Contributor
Publication
2002 - Alfred P. Sloan School of Management, Massachusetts Institute of Technology], [Cambridge, Mass, Massachusetts
Language
English
Word Count
3,000 words, Guess
Page Count
12 pages
Identifiers
- Internet Archivedatafusionthroug00putt
- OCLC Control Number50878132
- Open LibraryOL17936493M
Description
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. Keywords: Data Mining, Data Fusion, Leveraging of Sample Data.
Subjects
Series Statement
- Working paper -- 4342-02
- Working paper (Sloan School of Management) -- 4342.
Links
Other Editions
- Data fusion through statistical matching
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