A Cross-domain Temporal Interest Prediction Method by Integrating Social Information
[1]Hao Zhifeng,Shen policy,Cai Ruichu,et al.A Cross-domain Temporal Interest Prediction Method by Integrating Social Information[J].Journal of Zhengzhou University (Engineering Science),2019,40(02):51-57.[doi:10.13705/j.issn.1671-6833.2019.02.024]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
40
Number of periods:
2019 02
Page number:
51-57
Column:
Public date:
2019-03-19
- Title:
- A Cross-domain Temporal Interest Prediction Method by Integrating Social Information
- Keywords:
- interest prediction; Cross domain recommendation; social information; timing behavior; sequence learning
- CLC:
- -
- Abstract:
- Integrating user’s social information is an appropriate way to solve the user-cold start problem. Though various prediction models focus on integrating social relation information, few have noticed the dynamic change of the user’s interest. Thus, in this paper, we propose a cross-domain temporal interest prediction approach by integrating social activity information. First, we construct a cross-domain personized ranking model which can map the feature from social space into the purchase space. Further, we propose a feature modeling method based on data grouped by time period. Experiments on the dataset verify that the proposed method can predict user’s interest more effectively.
- References:
- -
- Similar References:
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Last Update:
2019-03-24
