• DocumentCode
    3461558
  • Title

    Data File Layout Inference Using Content-Based Oracles

  • Author

    Phillips, Reid A. ; Wing-Ning Li ; Thompson, Charlotte ; Deneke, Wesley

  • Author_Institution
    Comput. Sci. & Comput. Eng. Dept., Univ. of Arkansas, Fayetteville, AR, USA
  • fYear
    2013
  • fDate
    3-5 Dec. 2013
  • Firstpage
    1029
  • Lastpage
    1035
  • Abstract
    Data file layout inference refers to the problem of identifying the organizational characteristics associated with a structured text file, where every record in a text file shares the same structural properties. These properties include: character encoding, record length, field length (indicated by delimiting characters or fixed length), field position, and field semantic content. Within this paper, the above information is referred to as the layout of a file. This structural layout information is required to extract, transform, and load files into workflows within various data warehouse and data mining applications. A common need, layout inference is a manual, labor intensive process requiring human expertise whenever a file´s layout is unavailable, miscommunicated, or changed. This paper proposes an automated methodology for solving the layout inference problem by discovering the metadata of a structured text file and reports the results of a prototype system for real data files from customer data integration and management application.
  • Keywords
    data mining; file organisation; inference mechanisms; character encoding; content-based Oracles; customer data integration; data file layout inference; data mining; data warehouse; extract-transform-load; field length; field position; field semantic content; organizational characteristic; record length; structural layout information; structured text file; Context; Data mining; Encoding; Layout; Market research; Semantics; XML; combinatoric approach; content type; domain-specific software architecture; extract-transform-load (ETL); file layout inference; file processing; meta-data discovery; sampling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Engineering (CSE), 2013 IEEE 16th International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/CSE.2013.150
  • Filename
    6755331