Affiliations: [a] Provincial Key Laboratory of Informational Service for Rural Area of Southwestern Hunan, Shaoyang University, Shaoyang, Hunan, China
| [b] College of Information Engineering, Shaoyang University, Shaoyang, Hunan, China
Correspondence:
[*]
Corresponding author. Maolin Li, College of Information Engineering, Shaoyang University, Shaoyang, Hunan, China. E-mail: [email protected].
Abstract: Traditional information recommendation system using only the user’s score is calculated and recommended, although to a certain extent, can obtain the implied characteristics of users or resources, but the lack of enough semantic interpretation, affecting the effects of recommendation. This article studied and analyzed the recommendation based on attribute coupled matrix decomposition algorithm in the application of Internet of things, on the foundation of the matrix decomposition model successively introduced global offset and time offset, in order to improve the prediction accuracy and the quality is recommended. In this paper, the algorithm is proved by experiment and the prediction accuracy of the algorithm is improved.
Keywords: Property coupling, matrix decomposition, recommendation algorithm, internet
of things
