Semantic Data Matching: Principles and Performance

Russell Deaton, Thao Doan and Tom Schweiger
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Russell Deaton: Computer Science and Computer Engineering, University of Arkansas
Thao Doan: Computer Science and Computer Engineering, University of Arkansas
Tom Schweiger: Acxiom Corporation

Chapter 4 in Data Engineering, 2009, pp 77-90 from Springer

Abstract: Abstract Automated and real-time management of customer relationships requires robust and intelligent data matching across widespread and diverse data sources. Simple string matching algorithms, such as dynamic programming, can handle typographical errors in the data, but are less able to match records that require contextual and experiential knowledge. Latent Semantic Indexing (LSI)latent semantic indexing (LSI) (Berry et al. ; Deerwester et al. is a machine intelligence technique that can match data based upon higher order structure, and is able to handle difficult problems, such as words that have different meanings but the same spelling, are synonymous, or have multiple meanings. Essentially, the technique matches records based upon context, or mathematically quantifying when terms occur in the same record.

Keywords: Machine Intelligence Techniques; Simple String Matching Algorithm; Latent Semantic Indexing (LSI); Dispersed Data Sources; Higher Order Structure (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1007/978-1-4419-0176-7_4

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