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Study on Group Differences of Online Shopping Based on Data Mining

机译:基于数据挖掘的网上购物组差异研究

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摘要

In the face of complex problems of implementation intentions predict the online shopping behavior, we conducted a preliminary exploration of group differences intention on the online shopping behavior using data mining method. The research results show, different types of temperament, personality, gender and living area in online shopping experience and behavior intention have common characteristics of groups, and different groups have obvious difference in online shopping behavior. Finally, this paper combined with large data and the mobile Internet era characteristic, put forward to large data comprehensive online shopping search behavior index, 020 business model as the foundation, the prospect of research on the construction of implementation intention theory of online shopping behavior.
机译:面对实施意图的复杂问题预测在线购物行为,我们使用数据挖掘方法对网上购物行为进行了初步探索。研究结果表明,不同类型的气质,人格,性别和生活区在网上购物经验和行为意图具有群体的共同特征,不同的群体在线购物行为差异很大。最后,本文结合了大数据和移动互联网时代特征,提出大量数据综合网上购物搜索行为指数,020个商业模式作为基础,研究了在线购物行为的实施意图理论研究的前景。

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