Mining High-Utility Patterns in Marketing Datasets

Student: Ialnitskaia Viktoriia

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2017

This graduate paper presents a study of mining patterns with high utility in marketing datasets. Utility data mining is used for finding patterns that contribute to the highest utility in database. At present, the area of research of high utility patterns provides a wide range of algorithms. In this paper several existing algorithms such as association rules, frequent sets, high-utility itemsets are considered and their effectiveness is compared. In terms of practical application of these algorithms, the database of shopping baskets of children's clothing store was processed. Based on the identified patterns were constructed and compared three recommender systems.

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