A Novel Multi-user Itinerary Planning for Traveling Services

Objective: The main objective of this research is to generate and provide an optimized itinerary planning for the users with flight and hotel booking as per the user requirement to reach their satisfaction level. Methods: In this research, a novel fuzzy c means clustering is introduced for grouping and generating an optimal itinerary planning for the group of users. This work intends to satisfy the needs of all the users who are requesting for the itinerary plans with the satisfaction of their QoS requirement. To achieve this goal, the point of interest (POI) graphs will be constructed with the help of mapRedcue application which will simplify the processing of large amount of data’s. FCM algorithm is proved to be better clustering algorithm which considers the membership values among the various data points. So that the same data points can be clustered in the different cluster to which its membership value belongs. In our work we make sue use of this algorithm to cluster the users with the similar requirements. So that the same user request may clustered in different groups. Among that the optimized cluster of users with unique requirements can be selected for the itinerary planning construction. Results: FCM clustering used in the proposed approach for effective construction of the itinerary planning with the consideration of the users with similar requirement whereas in the existing work user similarity requirements are not considered. The experimental tests conducted were proves that the proposed methodology provides the optimized itinerary with the less time complexity and burden than the existing methodology. This performance analysis is done with the two performance metrics namely processing time and the weight ratio from which it can be proved that the proposed methodology provides better result. Conclusion: The findings demonstrate that the itinerary planning construction using FCM is presented and this method has high clustering accuracy than the previous methodologies.