基于大数据的在线学习行为分析模型研究

Study on online learning behavior analysis model based on big data

在现代市场营销中，利用大数据对客户行为进行在线学习实现精准营销，当前，移动信息技术的快速发展，基于移动网络的在线学习成为主流。通过使用元数据和社交网络分析，创建了新的指标来识别最有可能转化为移动互联网用户的客户，主要的指标为可自由支配的收入、时间和社会学习等；通过利用历史数据，对机器学习预测模型进行训练、验证，并用于选择实验组，选取在线客户的行为数据进行模型验证，结果证明该模式在较长期内也表现出良好的性能，在实验组中98％客户在活动结束后转化为最终的目标客户。

In the modern market marketing, customer behavior to make use of big data precision marketing, online learning at present, the rapid development of mobile information technology, based on the mobile network has become the mainstream of online learning. Through the use of metadata and social network analysis, create a new index to identify the most likely to be converted into mobile Internet users of the customer, the main index for discretionary income ,time and social learning, etc. ;By using historical data for machine learning model for training, validation, and is used to select the experimental group, the selection of online customer behavior data model validation, the results show that the model over the longer term also showed the good performance ,98% in the experimental group clients at the end of the activity into the ultimate goal.