In this paper, a recommender system for recommending flights to customers on the basis of user preferences, weightage technique and context aware system is proposed to help the consumers of service oriented environment to discover and select the most appropriate flight services from a large number of available ones. This recommender system provides the user with desired selection options, real-time information and recommends the user of itineraries that best fit his preferences, based on his previous purchases. These preferences are learnt from either explicit or implicit feedback provided by the user. But, past experiences show that that only a few numbers of users provide information about their preferences explicitly. The FRC uses implicit feedback to capture the preferences which are stored in the user’s profile for future personalized recommendations. The context aware method provides recommendations to the users regarding their environment and the details of the situation in which they are thus personalizing user’s experience. The proposed approach is yielded to overcome the problems caused by ignoring the contextual information. Most of the existing systems use the data from the individual user combined with the data from other users to make a recommendation. The current system only uses the data from the user to provide the feedback. This results in more personalized recommendation.


The content based approach, rather than looking for weight of one feature, calculates the over-all weight of the item in context, which is more important when the recommendation is based on several attributes. Hence this relates to comparing the current item against a case base and determining the overall weight and the status of the item in terms of recommendation.