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首页> 外文会议>PRICAI'98 : Topics in artificial intelligence >Data Mining for Risk Analysis and Targeted Marketing
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Data Mining for Risk Analysis and Targeted Marketing

机译：数据挖掘以进行风险分析和有针对性的营销

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摘要

Commercial databases often contain critical business information concerning past performance which could be used to predict the future. However, the huge amounts of data can make the extraction of this business information almost impossible by manual methods or standard software techniques. Data mining techniques can analyze, understand and visualize the huge amounts of stored data gathered from business applications and thus help companies stay competitive in today's marketplace. Currently, a number of data mining applications and prototypes have been developed for a variety of business domains. Most of these applications are targeted at predictive modeling that finds patterns of data to help predict the future trend and behaviors of some entities. Apart from predictive modeling, other data mining tasks such as summarization, association, classification and clustering could also be applied to business databases. In this paper, we will illustrate the different data mining tasks applied to a real-life business database for risk analysis and targeted marketing.
机译：商业数据库通常包含有关过去业绩的关键业务信息，这些信息可用于预测未来。但是，大量的数据几乎无法通过手动方法或标准软件技术来提取此业务信息。数据挖掘技术可以分析，理解和可视化从业务应用程序中收集的大量存储数据，从而帮助公司在当今市场上保持竞争力。当前，已经为各种业务领域开发了许多数据挖掘应用程序和原型。这些应用程序中的大多数都针对于预测模型，该模型查找数据模式以帮助预测某些实体的未来趋势和行为。除了预测建模之外，其他数据挖掘任务（例如摘要，关联，分类和聚类）也可以应用于业务数据库。在本文中，我们将说明应用于现实业务数据库以进行风险分析和目标市场营销的不同数据挖掘任务。

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