Analysis and FP-Growth Algorithm Design on Discount Data of Department Store Members
نویسندگان
چکیده
Abstract This paper mainly studies the discount data of department store members. The researsh shows that total supply discounted goods and number reward points issued have most significant relationship with customer activation rate, increase rate coverage scale would inactive members invalid score may a stronger incentive effect on active members, but it has no obvious ineffective In addition, by integrating commodity records each purchase, analyzing association rules, combinations associated consumption relationships are obtained, analysis model portfolio rules is established. based member information, sale water meter, detailed list, merchandise information table, through processing analysis, rejects abnormal data, prepares for following processing. By characteristics difference between non-member consumption, we can provide marketing suggestions manager FP-growth Algorithm designed to evaluate purchasing power their gender, length membership, age frequency, parameter explained, so as improve management level shopping mall. On this basis, Suggestions promotional activities in malls given.
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ژورنال
عنوان ژورنال: Lecture notes in electrical engineering
سال: 2022
ISSN: ['1876-1100', '1876-1119']
DOI: https://doi.org/10.1007/978-981-19-2456-9_80