Abstract
Usage of internet is growing rapidly and became more and more important in every aspect of life. Everyone is addicted to use the internet and enjoy its advantages. One of the key advantages with the internet is E-commerce. E-commerce being an online market facilitates the users to a greater extent. In the past, people used to buy the goods by going to the shops and markets but now everyone is using E-commerce to buy the goods. In past if people want to search for a product, they could directly ask the shop owner and he would provide it, if he had it. But in the E-commerce it is headache of the customer to search for the product as it is vast. To avoid this, recommendation systems are used. These recommendation systems recommend products for the users and help the users to take correct decision and also help for the growth of E-commerce. There are different types of recommendation systems such as content based, collaborative, hybrid etc. Variety of algorithms are been used by various researchers based on the application area and the requirements of the end user. In this paper, we propose a collaborative filtering recommendation system.
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RaviKanth, K., ChandraShekar, K., Sreekanth, K., Kumar, P.S. (2021). Recommendation System for E-Commerce by Memory Based and Model Based Collaborative Filtering. In: Abraham, A., Jabbar, M., Tiwari, S., Jesus, I. (eds) Proceedings of the 11th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2019). SoCPaR 2019. Advances in Intelligent Systems and Computing, vol 1182. Springer, Cham. https://doi.org/10.1007/978-3-030-49345-5_13
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DOI: https://doi.org/10.1007/978-3-030-49345-5_13
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