Frequent pattern found is one of the most important task in data mining,but the existing methods for mining of association rules are only single relationship-oriented or for some relatively simple models.This paper presents a new method that is effective for more complex model of relations.The algorithm of the method is also given.

For quickly locating the specific user groups in the mobile payment market, this paper investigates and analyzes the Mobile Ticketing in mobile payment service from five main aspects, the users awareness, demand, usage, using willingness and users evaluation. We use data mining methods of association rules to do analysis to 1615 valid questionnaires and locate the user groups who are most likely to use Mobile Ticketing, so as to help the Communication Carriers to lock the target customers market precisely and quickly at the beginning of promotional period of Mobile Payment. The results show that mobile payment market, especially mobile ticketing, is still in the early stage, the users are with low awareness, the potential user groups are very big, the users who are willing to use mobile payment services are mostly concentrate in young user groups with high spending monthly and high education.

Mining of Association Rules in the Multi-Relation Database

Citations

Research on User Groups Features of Mobile Payment: An Empirical Analysis Based on Association Rules of Data Mining

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