Version 1
: Received: 4 November 2017 / Approved: 6 November 2017 / Online: 6 November 2017 (06:36:37 CET)
How to cite:
Li, H.; Bian, Y.; Xu, X.; Sun, G. SRRTC: Social Recommendation Based on Relationship Transmission with Convergence Algorithm. Preprints2017, 2017110033. https://doi.org/10.20944/preprints201711.0033.v1
Li, H.; Bian, Y.; Xu, X.; Sun, G. SRRTC: Social Recommendation Based on Relationship Transmission with Convergence Algorithm. Preprints 2017, 2017110033. https://doi.org/10.20944/preprints201711.0033.v1
Li, H.; Bian, Y.; Xu, X.; Sun, G. SRRTC: Social Recommendation Based on Relationship Transmission with Convergence Algorithm. Preprints2017, 2017110033. https://doi.org/10.20944/preprints201711.0033.v1
APA Style
Li, H., Bian, Y., Xu, X., & Sun, G. (2017). SRRTC: Social Recommendation Based on Relationship Transmission with Convergence Algorithm. Preprints. https://doi.org/10.20944/preprints201711.0033.v1
Chicago/Turabian Style
Li, H., Xiuying Xu and Guozi Sun. 2017 "SRRTC: Social Recommendation Based on Relationship Transmission with Convergence Algorithm" Preprints. https://doi.org/10.20944/preprints201711.0033.v1
Abstract
Social recommendation is almost as the integration of the business platform and social platform, and gradually become a top in recommendation system. Social recommendation algorithm solves the problem of cold start and data sparseness for traditional commodity, while the internal structure of the relationship graph in social relations has not been fully excavated. This paper proposes two models of Micro Relation Transfer Model and Macro Relation Transfer Model of social relations, and applies the social relations transfer models into the social recommendation system. A relationship graph is built from the relationship between customers on the Internet. Micro Relation Transfer Model establishes the transfer activation function by calculating the relationship between the two customers using the similarity of interests set. Micro Relation Transfer Model spreads the relationship of friends by calculating the proportion of common neighbors held by the customer's social relations. In order to effectively control the transmission range and effect of social relations graph, we introduce pruning algorithm based on Monte Carlo Decision Tree convergence algorithm. The experimental results show that SRRTC algorithm enhances the success rate and stability significantly.
Keywords
social recommendation; relationship graph; micro relation transfer model; macro relation transfer model; monte carlo decision tree
Subject
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
