An Enhanced Approach for Tourism Recommendation System using Hybrid Filtering and Association Rule Mining

In the tourism recommendation system, thenumber of users and items is very large. But traditionalrecommendation system uses partial information foridentifying similar characteristics of users. Collaborativefiltering and content based filtering is the primaryapproach of any recommendation system. It provides arecommendation which is easy to understand. It is basedon similarities of user opinions like rating or likes anddislikes and content based filtering is used to provideopinion for the new users profile. So the recommendationprovided by collaborative and content cannot beconsidered as quality recommendation. Recommendationafter association rule mining is having high support andconfidence level. So that it will be considered as strongrecommendation. The hybridization of both hybridfiltering and association rule mining can produce strongand quality recommendation even when sufficient dataare not available. This paper combines recommendationfor tourism application by using a hybridization oftraditional collaborative and content filtering techniquesand data mining techniques.