Title
Application of recommendation system: an empirical study of the mobile reading platform
Abstract
Mobile reading on 'smart' terminals (like smartphones and tablet computers)is an increasing popular subject, and the recommendations of e-books for users also begin to attract more attentions. In this paper, we mainly demonstrate the performance of the personalized recommendation on the mobile reading platform, based on the analysis of the reading records on mobile phones. The analysis results of the feedback of users for the recommendations show that the personalized recommendation based on the mass diffusion algorithm is much better than the algorithm of the mobile company used before. In particular, both the number of the motivated page views and the motivated users have a dramatically increase. All these results indicate that the mass diffusion algorithm has an outstanding performance on the mobile reading recommendation, which can help users quickly find the books they are interested in. Meanwhile, it help the company enlarge the customer volume and improve the customer experience.
Year
DOI
Venue
2012
10.1007/978-3-642-34624-8_45
ISMIS
Keywords
Field
DocType
analysis result,mobile company,mass diffusion algorithm,customer experience,personalized recommendation,recommendation system,mobile reading recommendation,mobile reading,mobile phone,reading record,mobile reading platform,empirical study
Recommender system,World Wide Web,Mobile search,Computer science,Customer experience,Mobile Web,Page view,Multimedia,Empirical research
Conference
Citations 
PageRank 
References 
0
0.34
10
Authors
4
Name
Order
Citations
PageRank
Chun-Xiao Jia101.01
Chuang Liu200.34
Run-Ran Liu363.00
Peng Wang45010.52