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Interesting User Behaviour Prediction in Mobile E-commerce Environment using Constraints

ABSTRACT Mobile e-commerce has become a more emerging topic these days and is speedily increasing with the growth of internet. It is playing an essential role in our life as it helps us by using new trends and technologies to improve business and thus providing quicker information. Behaviour analysis and sequence pattern prediction provide scope for more advanced research topics. If a user finds various interesting sequences in mobile e-commerce environment, then she/he can predict lots of new information. This predicted information may be useful for defining various new services or improving on existing and may also be useful to manage service infrastructure to offer quicker responses. Today, user behaviour sequence mining is an emerging issue in mobile e-commerce environment which considers mobile user services, accessing sequences at various locations on different times. In the current scenario, the user may only be interested in the service sequences with some specific constraints. The constraint may define to the type of service or importance of a particular service. Here, we consider important or useful services for particular user in mobile e-commerce environment. We proposed an efficient framework, namely CIUBSM (Constraint based Interesting User Behaviour Sequence Mining) which deals with important constraint of services and generates an interesting behaviour sequence of mobile users. Experimental results show that the proposed framework is better than previous constraint-based frameworks.