DocumentCode
2990221
Title
Research on personalized recommendation model for mobile advertising
Author
Gu Qi-wei ; Guo Peng
Author_Institution
Coll. of Manage., Shenzhen Univ., Shenzhen, China
fYear
2012
fDate
20-22 Sept. 2012
Firstpage
59
Lastpage
63
Abstract
Aimed at enhancing the accuracy of the personalized recommendation for mobile advertising, overcoming the shortcomings of the traditional similarity calculation and collaborative filtering recommendation techniques, the cloud model calculation method improved the strict item or project matching problem in traditional similarity calculation, resolved extreme sparse data problem. And a mixed recommendation model is established based on mobile advertisement, content recommendation and linear combination of collaborative filtering recommendation. Experiments prove that the new method has obviously smaller MAE and higher quality in recommendation system.
Keywords
advertising; cloud computing; collaborative filtering; mobile computing; recommender systems; cloud model calculation method; collaborative filtering recommendation techniques; content recommendation; extreme sparse data problem; linear combination; mixed recommendation model; mobile advertisement; mobile advertising; personalized recommendation model; project matching problem; similarity calculation; strict item; Advertising; Collaboration; Computational modeling; Educational institutions; Filtering; Mobile communication; Predictive models; E-commerce; cloud model; mixed recommendation; mobile advertising; recommendation system;
fLanguage
English
Publisher
ieee
Conference_Titel
Management Science and Engineering (ICMSE), 2012 International Conference on
Conference_Location
Dallas, TX
ISSN
2155-1847
Print_ISBN
978-1-4673-3015-2
Type
conf
DOI
10.1109/ICMSE.2012.6414161
Filename
6414161
Link To Document