Institute of Transportation, MOTC

       Nowadays, the international cruise market develops rapidly. The number of people taking cruises to Asia increases gradually. The Taiwan Ministry of Transportation and Communication has planned Keelung port to be the main international port of call. After cruises stop at Keelung port, individual tourists will travel around Taipei and Keelung. Because some of the foreign tourists don’t have enough tourist information of Taiwan or don’t know much about Taiwan, it is not easy for them to find attractions which match their preference. Keelung port also lacks of the information equipment and systems.
In this research, we will use collaborative filtering to build a tourism recommendation system for cruise individual passengers. After using this system, cruise individual passengers can save time for finding attractions. The system will recommend attractions which match their preference and plan a tour through genetic algorithm. According to our results, our recommendation model and system can provide more convenient and satisfying tour planning services.