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New methods for analysing marketing Databases in the age of digital media

New methods for analysing marketing Databases in the age of digital media
数字媒体时代分析营销数据库的新方法
批准号:
DP1094289
负责人:
Prof Michael Smith
金额:
$32.38万
依托单位:
依托单位国家:
澳大利亚
项目类别:
Discovery Projects
财政年份:
2010
资助国家:
澳大利亚
项目状态:
已结题
起止时间:
2010-01-01 至 2014-03-01

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中文摘要
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英文摘要
This is a time of enormous and rapid change in many areas of Australian business due to the introduction and widespread dissemination of digital media. It has resulted in the accumulation of large integrated databases of customer information and their transactions. Firms in all countries, particularly those challenged by distance and size, like Australia, are now seeking to find ways to make better use of their voluminous information so as to make efficiency gains in their business processes, strategic decision-making and customer relationship management. Our project aims to contribute to the ARC priority research goal of smart information use by developing new methodologies for the analysis of these large integrated databases.
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Bayesian copula modelling of multivariate dependence: getting to grips with data that is far from normal
  • 批准号:
    FT110100729
  • 项目类别:
    ARC Future Fellowships
  • 资助金额:
    $53.79万
  • 财政年份:
    2012
  • 负责人:
    Prof Michael Smith
  • 依托单位:
Bayesian estimation of flexible spatial models with applications in medical imaging and econometric modeling
  • 批准号:
    DP0452777
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $4.87万
  • 财政年份:
    2004
  • 负责人:
    Prof Michael Smith
  • 依托单位:
Reasons and Rationality
  • 批准号:
    DP0343704
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $8.82万
  • 财政年份:
    2003
  • 负责人:
    Prof Michael Smith
  • 依托单位:
Reasons and Rationality
  • 批准号:
    ARC : DP0343704
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $19.5万
  • 财政年份:
    2003
  • 负责人:
    Prof Michael Smith
  • 依托单位:
国内基金
海外基金
复杂图像处理中的自由非连续问题及其水平集方法研究
  • 批准号:
    60872130
  • 项目类别:
    面上项目
  • 资助金额:
    28.0万元
  • 批准年份:
    2008
  • 负责人:
    刘国才
  • 依托单位:
Computational Methods for Analyzing Toponome Data