Abstract
In modern society, online purchasing using popular website has become a new trend and the reason beyond it is E-commerce business which has grown rapidly. These E-commerce systems cannot provide one to one recommendation, due to this reason customers are not able to decide about products, and they may purchase. The main concern of this work is to increase the product sales, by keeping in mind that at least our system may satisfy the needs of regular customers. This paper presents an innovative approach using collaborative filtering (CF) and artificial neural networks (ANN) to generate predictions which may help students to use these predictions for their future requirements. In this work, buying pattern of the students who are going to face campus interviews has been taken into consideration. In addition to this, buying patterns of the alumni for luxurious items was also considered. This recommendation has been done for the products, and the results generated by our approach are quite interesting.
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Bandyopadhyay, S., Thakur, S.S. (2020). Product Prediction and Recommendation in E-Commerce Using Collaborative Filtering and Artificial Neural Networks: A Hybrid Approach. In: Mandal, J., Sinha, D. (eds) Intelligent Computing Paradigm: Recent Trends. Studies in Computational Intelligence, vol 784. Springer, Singapore. https://doi.org/10.1007/978-981-13-7334-3_5
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DOI: https://doi.org/10.1007/978-981-13-7334-3_5
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