Abstract
The exponential rise of the e-commerce market in today’s times has marked the necessity for efficient recommendation systems. Corporate giants are heavily relying on them for hitting higher revenues. This paper proposes an efficient hybrid algorithm, aimed at helping the online apparel retail market. It combines the advantages of frequency-based search and semantic-based search. This paper then goes on to compare the outcomes of the designed algorithm with other state-of-the-art algorithms that are currently being used in recommendation systems.
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Meel, P., Chawla, P., Jain, S., Rai, U. (2021). Hybrid Apparel Recommendation System Based on Weighted Similarity of Brand and Colour. In: Gupta, D., Khanna, A., Bhattacharyya, S., Hassanien, A.E., Anand, S., Jaiswal, A. (eds) International Conference on Innovative Computing and Communications. Advances in Intelligent Systems and Computing, vol 1165. Springer, Singapore. https://doi.org/10.1007/978-981-15-5113-0_32
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DOI: https://doi.org/10.1007/978-981-15-5113-0_32
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