Abstract

• Mobile commerce (m-commerce) is the delivery of electronic commerce capabilities directly into the consumer’s hand, anywhere and anytime via wireless technology. Mobile phones are becoming a primary platform for accessing information and when coupled with recommendation systems technologies they can become key tools for mobile users both for leisure and business applications. Also, the huge amount of data in mobile business processes and physical limitations have increased the importance of personalization process. The users are flooded with so much of choices that it is hard for them to find appropriate and suitable items in m-commerce. Recommendation system can aid users in discovering information or items in a personalized manner. A mobile-based tourism recommendation system can help customers in travel planning because it may be so complicated and confusing to process a lot of information on the travel sites. Collaborative filtering method compares the user’s past ratings with those of other users (neighbors) to find users with similar preferences. Highly rated items by these neighbors will be recommended. In this research, the system suggests personalized travel locations to users based on their rating profiles and interests by using collaborative filtering method.