CAJ | 학술논문

　　分析了大数据环境下的O2 O电商用户数据特征，提出O2 O电商用户数据挖掘框架，并探讨数据挖掘流程和主要的数据挖掘方法，分别从O2 O电商平台、O2 O用户和O2 O商家三者角度探讨了O2 O电商用户数据挖掘的应用问题。研究认为：O2 O用户数据挖掘框架包括数据来源层、数据收集层、数据组织层、数据分析层与数据应用层等层级；数据挖掘流程主要包括数据收集、数据预处理、数据挖掘及数据应用4个过程；O2 O电商用户数据的挖掘应用包括精准营销、平台网站优化、欺诈分析与防范、个性化推荐、增值服务开发与产品创新等方面。
　　분석료대수거배경하적O2 O전상용호수거특정，제출O2 O전상용호수거알굴광가，병탐토수거알굴류정화주요적수거알굴방법，분별종O2 O전상평태、O2 O용호화O2 O상가삼자각도탐토료O2 O전상용호수거알굴적응용문제。연구인위：O2 O용호수거알굴광가포괄수거래원층、수거수집층、수거조직층、수거분석층여수거응용층등층급；수거알굴류정주요포괄수거수집、수거예처리、수거알굴급수거응용4개과정；O2 O전상용호수거적알굴응용포괄정준영소、평태망참우화、기사분석여방범、개성화추천、증치복무개발여산품창신등방면。
In this paper, not only the characters of O2O EC user data but also their data mining framework, procedure and the main methods are analyzed. And the application issue of O2O EC user data mining is highlighted from the perspective of O2O EC platform enterprises, O2O users, and O2O merchants. By theoretical analysis, the paper gets the following conclusions. Mining framework of O2O user data consists of data sources layer, data collection layer, data organization layer, data analysis layer and data application layer. Data mining process includes data collection, data preparation, data mining and data application. The O2O user data mining can put forward precision marketing, platform website optimization, fraud analysis and precaution, personalized recommendation, the development of value-added services and product innovation based on mining result.