Research on Personalized Recommendation Model Based on Dynamic Interestingness for Online Hotel Reservation

This paper analyzes the status in quo and insufficient of personalized recommendation of domestic representational online hotel reservation Websites, and presents a personalized recommendation system model based on dynamic interestingnesss for browsers. After having normalized and analysis of users' online browsing behavior, using clustering technique to find users' preferences, it can recommend the hotels to browsers. In the strategy selection process, the model is emphasis on the dynamic characteristics of interest preference during the browse, combined with dynamic interestingness in reliability and cost-effective to recommend, the effectiveness of the recommendation has been improved. Finally, Matlab simulation tool is used to calculate the result of online hotel reservations recommended programs based on current users' dynamic interestingness .