Abstract
Recommender system have broad and powerful applications in e-commerce, news promotion and online education. As we all know, the user’s rating behavior is generally determined by subjective preferences and objective conditions. However, all the current studies are focused on subjective preferences, ignoring the role of the objective conditions of the user. The user purchasing power based on price is the key objective factor that affects the rating behavior and even purchasing decision. Users’ purchasing decisions are often affected by the purchasing power, and the current researches did not take into account the problem. Thus, in this paper, we consider the influence of user preferences and user purchasing power on rating behavior simultaneously. Then, we designed a reasonable top-N recommendation strategy based on the user’s rating and purchasing power. Experiments on Amazon product dataset show that our method has achieved better results in terms of accuracy, recall and coverage. With ever larger datasets, it is important to understand and harness the predictive purchasing power on the users’ rating behavior and purchasing decisions.
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Acknowledgements
This work is supported by “Fundamental Research Funds for the Central Universities” (XDJK2017C027) and “CERNET Innovation Project” (NGII20170516).
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Wang, Y., Xu, X., He, J., Chen, C., Ren, K. (2018). Impact of Purchasing Power on User Rating Behavior and Purchasing Decision. In: Tan, Y., Shi, Y., Tang, Q. (eds) Advances in Swarm Intelligence. ICSI 2018. Lecture Notes in Computer Science(), vol 10942. Springer, Cham. https://doi.org/10.1007/978-3-319-93818-9_39
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DOI: https://doi.org/10.1007/978-3-319-93818-9_39
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