To find out which product should be recommended to the customer and when to recommend is done by the recommender system. Different approaches by using customer profile and product description are used to build recommender system. Although these information are not enough to recommend, sometimes buying of some products occurs in a stepwise manner, where buying of one product follows the buying of other products. The purpose of this research is to find the sequences followed by customers while purchasing products to improve the efficiency of recommender system. Sequence pattern mining is used to find out the order of purchasing products. The duration we find tells the time gap between the purchased product and recommendation of next sequential products.
CITATION STYLE
Saini, S., Saumya, S., & Singh, J. P. (2017). Sequential purchase recommendation system for E-commerce sites. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10244 LNCS, pp. 366–375). Springer Verlag. https://doi.org/10.1007/978-3-319-59105-6_31
Mendeley helps you to discover research relevant for your work.