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Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Kseniya Titova
Frequent Itemset and Association Rules for E-Commerce
8
2016
In this paper we researched online-store data of purchases, made a search and analysis of frequent itemsets. As the result we established interrelationship between items, which are usually purchased together. This interrelationship can be used as the base for a recommender system. Besides, using the special software, we conduct the analysis and reorganization of online-store carts’ database. We made an association and general association rules search with help of special algorithms. Also we made overview of theoretical base of all involved methods. For the association and general association rules search SPMF software was used.

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