Effective User Invitation Models for Online Survey Using Clustering Algorithm
With the continuous and rapid development of online questionnaire survey,the low response rate has plagued operating companies.To solve this problem,this paper proposed an effective user invitation model by our improved clustering algorithm,which analyzed large-scale historical user behavior characteristic data,including users quality data,users preferential data and users similarity data.Extensive experiments with large-scale data from an online survey company have been conducted to validate the feasibility and effectiveness of our proposed approach.Experimental results demonstrate that the questionnaire response rate is increased and our approach can be easily deployed in real-world online survey application for effective personalized survey recommendation.
online questionnaire survey clustering algorithm user invitation model response rate
Sen Shao Shaochun Wu Guobing Zou Liang Chen
School of Computer Engineering and Science, Shanghai University Shanghai 200444, China
国际会议
秦皇岛
英文
1445-1449
2015-09-18（万方平台首次上网日期，不代表论文的发表时间）