Abstract
With the development of e-commerce technology, a growing number of people prefer to purchase clothes on the e-commerce websites. Therefore, an effective recommendation system is necessary for customers. User-based Collaborative Filtering (UCF) algorithm is widely utilized to predict the preferences of customers. However, UCF algorithm employs the sparse matrix and the recommendation has low precision. In this paper, an improved recommendation algorithm named Advanced User-based Collaborative Filtering (AUCF) algorithm is proposed and implemented in the clothing recommendation system. The proposed AUCF algorithm introduces user-item linked list, which can overcome the problem of large time complexity. Considering the impact of different popularity of items, AUCF algorithm is capable of publishing the negative influence of popular items, which can increase the recommendation coverage. Experiment results show the AUCF algorithm significantly increases the recommendation coverage and precision.
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References
Liu, Y., Xu, L., Chen, Y., Fan, Y., Xu, B., Nie, J.: A novel power control mechanism based on interference estimation in LTE cellular networks. In: 16th IEEE International Symposium on Communications and Information Technologies, pp. 397–401. IEEE Press, Qingdao (2016)
Cao, Y., Wang, N., Sun, Z., Cruickshank, H.: A reliable and efficient encounter-based routing framework for delay/disruption tolerant networks. IEEE Sens. J. 15(7), 4004–4018 (2015)
Xu, L., Chen, Y., Gao, Y., Cuthbert, L.: A self-optimizing load balancing scheme for fixed relay cellular networks. In: 2th IET International Conference on Communication Technology and Application, pp. 306–311. IET Press, Beijing (2011)
Wang, W., Xu, L., Zhang, Y., Zhong, J.: A novel cell-level resource allocation scheme for OFDMA system. In: 1st International Conference on Communications and Mobile Computing, pp. 287–292. IET Press, Kunming (2009)
Xu, L., Cheng, X., Liu, Y., Chen, W., Luan, Y., Chao, K., Yuan, M., Xu, B.: Mobility load balancing aware radio resource allocation scheme for LTE-advanced cellular networks. In: 16th IEEE International Conference on Communication Technology, pp. 806–812. IEEE Press, Hangzhou (2015)
Cao, Y., Sun, Z., Wang, N., Riaz, M., Cruickshank, H., Liu, X.: Geographic-based spray-and-relay (GSaR): an efficient routing scheme for DTNs. IEEE Trans. Veh. Technol. 64(4), 1548–1564 (2015)
Xu, L., Luan, Y., Cheng, X., Xing, H., Liu, Y., Jiang, X., Chen, W., Chao, K.: Self-optimised joint traffic offloading in heterogeneous cellular networks. In: 16th IEEE International Symposium on Communications and Information Technologies, pp. 263–267. IEEE Press, Qingdao (2016)
Cao, Y., Wang, T., Kaiwartya, O., et al.: An EV charging management system concerning drivers’ trip duration and mobility uncertainty. IEEE Trans. Syst. Man Cybern. Syst. PP(99), 1 (2016)
Xu, L., Luan, Y., Cheng, X., Cao, X., Chao, K., Gao, J., Jia, Y., Wang, S.: WCDMA data based LTE site selection scheme in LTE deployment. In: 1st International Conference on Signal and Information Processing, Networking and Computers, pp. 249–260. CRC Press Taylor & Francis Group, Beijing (2015)
Chinese Ecommerce Research Centre. http://www.100ec.cn/. Accessed 5 June 2017
Guo, G., Zhang, J., Zhu, F., Wang, X.: Factored similarity models with social trust for top-N item recommendation. Knowl. Based Syst. 122, 17–25 (2017)
Wang, W., Zhang, G., Lu, J.: Member contribution-based group recommender system. Decis. Support Syst. 87, 80–93 (2016)
Fulton, W.: Intersection Theory, 2nd edn. Springer, New York (1998)
Xu, L., Cheng, X., Chen, Y., Chao, K., Liu, D., Xing, H.: Self-optimised coordinated traffic shifting scheme for LTE cellular systems. In: 1st EAI International Conference on Self-Organizing Networks, pp. 67–75. Springer Press, Beijing (2015)
Cao, Y., Sun, Z., et al.: Routing in delay/disruption tolerant networks: a taxonomy, survey and challenges. IEEE Commun. Surv. Tutor. 5(12), 654–677 (2013)
Zhang, X., Wang, N., Cao, Y., et al.: A stochastic analytical modelling framework on ISP-P2P collaborations in multi-domain environments. IEEE Syst. J. PP(99), 1 (2016)
Xu, L., Luan, Y., Cheng, X., Fan, Y., Zhang, H., Wang, W., He, A.: Telecom big data based user offloading self-optimisation in heterogeneous relay cellular systems. Int. J. Distrib. Syst. Technol. 8(2), 27–46 (2017)
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Liu, Y., Nie, J., Xu, L., Chen, Y., Xu, B. (2018). Clothing Recommendation System Based on Advanced User-Based Collaborative Filtering Algorithm. In: Sun, S., Chen, N., Tian, T. (eds) Signal and Information Processing, Networking and Computers. ICSINC 2017. Lecture Notes in Electrical Engineering, vol 473. Springer, Singapore. https://doi.org/10.1007/978-981-10-7521-6_53
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DOI: https://doi.org/10.1007/978-981-10-7521-6_53
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