The Mobile Personalized Recommendation Model Containing Implicit Intention

• 作者: Caixue Zheng Jing Liu Jun Zhang Shuqun He Yan Li
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: MOBILE e-commerce·Personalized recommendations·Hidden wishes·Big data INTELLIGENCE platform
• 年，卷（期）: 2015,（B12）
• 页码范围: 8-9
• 页数: 2页
• 分类号: C5

摘要

Because mobile e-commerce is limited by the mobile terminal,network environment and other factors,accurate personalized recommendations become more and more important.We establish a large data intelligence platform,aiming at the characteristics of mobile e-commerce;we put forward a personalized recommendation model with implicit intention further.Firstly,create an intelligence unit with the virtual individual association set,virtual demand association set and virtual behavior associated set;Secondly,calculate the complex buying behavior prediction engine;Finally,give the predictive value of complex buying behavior.This method takes full account of factors such as hidden wishes perturbations that affect the predict of complex buying behavior,which to some extent solve a long-span composite purchasing behavior prediction.It shows that this method improves the purchasing behavior prediction accuracy effectively through experiments.