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Recent Advances In Data Mining Of Enterprise Data: Algorithms And Applications

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Title: Recent Advances In Data Mining Of Enterprise Data: Algorithms And Applications
Description: The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as “enterprise data”. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making.
Authors: Evangelos Triantaphyllou, T Warren Liao
Resource Type: eBook.
Subjects: Business enterprises--Data processing--Congresses, Data mining--Congresses
Categories: COMPUTERS / Artificial Intelligence / General, BUSINESS & ECONOMICS / Production & Operations Management, COMPUTERS / Data Science / Data Analytics
Database: eBook Collection (EBSCOhost)
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  Data: Recent Advances In Data Mining Of Enterprise Data: Algorithms And Applications
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  Data: The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as “enterprise data”. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making.
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  Data: <searchLink fieldCode="AR" term="%22Evangelos+Triantaphyllou%22">Evangelos Triantaphyllou</searchLink><br /><searchLink fieldCode="AR" term="%22T+Warren+Liao%22">T Warren Liao</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Business+enterprises--Data+processing--Congresses%22">Business enterprises--Data processing--Congresses</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining--Congresses%22">Data mining--Congresses</searchLink>
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  BibEntity:
    Classifications:
      – Code: 006.312
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Business enterprises--Data processing--Congresses
        Type: general
      – SubjectFull: Data mining--Congresses
        Type: general
    Titles:
      – TitleFull: Recent Advances In Data Mining Of Enterprise Data: Algorithms And Applications
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Evangelos Triantaphyllou
      – PersonEntity:
          Name:
            NameFull: T Warren Liao
      – PersonEntity:
          Name:
            NameFull: Evangelos Triantaphyllou
      – PersonEntity:
          Name:
            NameFull: T Warren Liao
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2008
            – D: 04
              M: 02
              Type: profile
              Y: 2014
          Identifiers:
            – Type: isbn-print
              Value: 9789812779854
            – Type: isbn-electronic
              Value: 9789812779861
          Numbering:
            – Type: volume
              Value: 00006
          Titles:
            – TitleFull: Recent Advances In Data Mining Of Enterprise Data: Algorithms And Applications
              Type: main
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