Abstract
In this paper, we address the problem of identifying target user through the model of computing user preference for a certain item or service. The model we present works for a specific domain through online behavior analysis which considers user’s attentiveness of the entire area and the specific item combination style combining features of the specific industry. The model is evaluated by predicting users’ behavior and advertising click-through rate in the real application environment. The results show that this model is successful in precision recommendation, especially for the dynamic data analysis.
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Acknowledgements
This work was partially supported by GDNSF fund (2015A030313782), SUSTech Starup fund (Y01236215), SUSTech fund (05/Y01051814, 05/Y01051827, 05/Y01051830, and 05/Y01051839).
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Jiang, S., Luo, Z., Huang, Z., Liu, J. (2019). A Model for Computing User’s Preference Based on EP Algorithm. In: Panigrahi, B., Trivedi, M., Mishra, K., Tiwari, S., Singh, P. (eds) Smart Innovations in Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 670. Springer, Singapore. https://doi.org/10.1007/978-981-10-8971-8_11
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DOI: https://doi.org/10.1007/978-981-10-8971-8_11
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