Tourism industry is one of the most rapidly growing industry in the world. It has major contribution to the economy of the country. Through literature survey, it has been observed that there is much scope of improvement in this sector. This paper presents the tourism recommendation system which is built using the concept of web mashup which extracts data from multiple websites. This extracted data is used for analysis and providing recommendation about the touristic spots to the users. Recommendation uses components from tourist database, namely restaurant id, place id, hotel id, event id as item sets for performing apriori algorithm. The antecedents are matched with the last transaction of the logged in user and the precedents are displayed.