A Framework of Mobile Context-Aware Recommender System

• 作者: Caihong Liu Chonghui Guo
• 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 CONTEXT-AWARE Long-term BEHAVIOR PATTERN SHORT-TERM BEHAVIOR PATTERN RECOMMENDATION system
• 年，卷（期）: 2017,（2）
• 页码范围: 18-21
• 页数: 4页
• 分类号: C5

摘要

Mobile users can be recommended services or goods precisely according to their actual needs even in different contexts. Therefore, it is necessary to construct a framework integrating following functions: context identification,context reasoning, services or product recommendations and other tasks for the mobile terminal. In this paper, we firstly introduce mobile context awareness theory, and describe the composition of context-aware mobile systems. Secondly, we construct a framework of mobile context-aware recommendation system in line with the characteristics of mobile terminal devices and mobile context-aware data. Then, we build a nested key-value storage model and an up-to-date algorithm for mining mobile context-aware sequential pattern,in order to find both the user’s long-term behavior pattern and the new trend of his recent behavior, to predict user’s next behavior. Lastly, we discuss the difficulties and future development trend of mobile context-aware recommendation system.