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大数据时代下的情报分析与挖掘技术研究——电信客户流失情况分析 被引量:20

Research on Information Analysis and Data Mining in the Age of Big Data:Analysis of Customer Loss in Telecom
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摘要 大数据时代下的信息具有体量大、复杂性高、更新速度快的特点,从具有如此复杂特性的信息中挖掘出用户所需的情报,难度较以往有了很大的提升。要在发展中抢占先机,在大数据时代获取竞争优势,就必须对原有的情报分析思路进行必要的升级改造,以满足信息的情报属性。文章在介绍了大数据以及大数据环境下情报内涵转变的原因之后,提出了一种在大数据背景下的情报分析与挖掘的建模机理,首先应用MapReduce建立情报任务分解概念模型,然后针对分解后的某一单任务数据表进行预处理和数据挖掘工作,利用数学模型、人工智能等方法构造大数据时代下情报分析与数据挖掘的新思路。最后利用仿真实验来验证这一新思路的可行性和合理性。 Large scale, high complexity and update fast are three characteristic of information under the age of big data, the difficulty of mining valuable information form such complex data set has been greatly improved. In order to seize the opportunity in development and gain competitive advantage under the age of big data, it is must to update the original information analysis method and meet the data satisfy the information attribute. Based on the introduction of big data and the change reason of information content under the age of big data, this paper put forward a modeling mechanism of information analysis and mining under the age of big data, the modeling mechanism is, first, construct the model of task decomposition of information by MapReduce tool, then, make data preprocessing and mining operation according to the single task data sheet, use mathematical model, artificial intelligence and other methods to construct the new ideas of information analysis and data mining under the age of big data, finally, a case study presented to demonstrate the feasibility and rationality of our approach.
出处 《情报学报》 CSSCI 北大核心 2013年第6期564-574,共11页 Journal of the China Society for Scientific and Technical Information
基金 国家自然科学基金项目(71101041) 高等学校优秀人才基金项目(2012SQRL009) 国家级创新计划项目(111035954)
关键词 情报 大数据 数据挖掘 任务分解 MAPREDUCE information, big data, data mining, task decomposition, MapReduce
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