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  • Articles and reports: 12-001-X20040027750
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    Intelligent Character Recognition (ICR) has been widely used as a new technology in data capture processing. It was used for the first time at Statistics Canada to process the 2001 Canadian Census of Agriculture. This involved many new challenges, both operational and methodological. This paper presents an overview of the methodological tools used to put in place an efficient ICR system. Since the potential for high levels of error existed at various stages of the operation, Quality Assurance (QA) and Quality Control (QC) methods and procedures were built into this operation to ensure a high degree of accuracy in the captured data. This paper describes these QA / QC methods along with their results and shows how quality improvements were achieved in the ICR Data Capture operation. This paper also identifies the positive impacts of these procedures on this operation.

    Release date: 2005-02-03
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  • Articles and reports: 12-001-X20040027750
    Description:

    Intelligent Character Recognition (ICR) has been widely used as a new technology in data capture processing. It was used for the first time at Statistics Canada to process the 2001 Canadian Census of Agriculture. This involved many new challenges, both operational and methodological. This paper presents an overview of the methodological tools used to put in place an efficient ICR system. Since the potential for high levels of error existed at various stages of the operation, Quality Assurance (QA) and Quality Control (QC) methods and procedures were built into this operation to ensure a high degree of accuracy in the captured data. This paper describes these QA / QC methods along with their results and shows how quality improvements were achieved in the ICR Data Capture operation. This paper also identifies the positive impacts of these procedures on this operation.

    Release date: 2005-02-03
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