Traveler's Recommendation System Using Data Mining Techniques

Nowadays, Recommender Systems are being used in multiple different domains. This paper mainly focuses on application of recommendation system in tourism. For planning a trip tourists usually searches for destination information like reviews, route from source to destination, start time, end time, address, accommodations, nearby attractions, etc. Sometimes tourists may consult travel agencies to plan their trip. Tourist has to plan their trip according to agencies available packages. Each tourist's interest and need are not considered when trip is planned by travel agencies. People in agencies convince tourist for their packages even if tourists are not interested. Generalized packages are offered by travel agencies and does not give freedom to tourist to choose their hotels, restaurants according to their choice and need. To solve this problems we propose a system in which tourists will define their need, interest, hobbies then system provide recommendations like best places to travel which are nearer to his current location, points according to season, hotels, route based on his/her interest, so that tourist can plan their own trip. This system is also providing which places are mostly visited by other tourists and reviews of the places by other tourist who has visited that place, so that it will help tourist to decide place to visit.