基于用户行为模型的移动APP信息采集方法

MOBILE APP INFORMATION COLLECTION METHOD BASED ON USER BEHAVIOR MODEL

传统Web数据采集的网络蜘蛛模型无法持续高效采集移动客户端数据信息,满足不了现有的舆情行业获取飞速增长的移动客户端信息的迫切需求。针对移动客户端信息采集设置的诸多限制,提出基于多用户访问模型和多IP模型的采集方案。对采集程序进行调整改进,并针对采集效率进行测试和分析。测试结果基本满足现有的对新闻移动APP客户端信息采集的实时性和全面性的要求,达到实际应用的标准。

Because the traditional Web data collection web spider model cannot continuously and efficiently collect mobile client data information and cannot meet the urgent needs of the existing public opinion industry to obtain the rapidly growing mobile client information,we proposed a scheme of collecting information based on network agents with multi browser and IP address for many of the limitations set by mobile clients for information gathering. We adjusted and improved the collection procedure and tested and analysed the acquisition efficiency. The test results basically meet the existing real-time and comprehensive requirements for news mobile APP client information collection,and reach the standards of practical application.