基于C4.5算法和Hadoop云计算平台的购物意愿分析方法

Analytic Method of Customers' Shopping Intention Based on C4.5 Algorithm and Hadoop Platform

为适应大数据背景下的计算需求,首先根据C4.5算法计算原理的特点,对C4.5进行数据处理并行化改进。然后根据Hadoop云平台的特点,对数据处理流程进行简要说明。最后,通过搭建Hadoop云平台环境,使用随机生成的测试数据集对算法进行验证。分析消费者可能购买的商品,实现数据的利用率最大化、提高交易成交率和挖掘潜在交易。通过实验分析得出,基于C4.5算法和Hadoop云计算平台的购物意愿分析方法可以应用到大型电商平台对消费者的购物意愿进行分析中。

To meet the demand of big data computing, firstly, according to the characteristics of the C4.5 algorithm calculation principle, data processing was carried out on the C4.5 parallelization improvement. Then, considering the features of Hadoop platform, the data processing is explained briefly in this paper. Finally, the experiment used the randomly generated test data sets to verify the algorithm in the Hadoop cloud platform. The method not only helps us to identify customers＇ willingness of shopping and realize maximum use of data, it also provides an approach to improve the trade rates and excavate potential deals. According to experimental analysis, the method can be applied to large electric business platform to analyze consumers＇ willingness of shopping.