Tourism Destination Recommendation and Marketing Model Analysis Based on Collaborative Filtering Algorithm

The Internet has penetrated into all fields. As the most dynamic “sunrise industry,” tourism also been swept such a wave of Internet. In an era “information overload,” how to find one’s favorite attractions among massive tourist become difficult problem. order solve this problem, personalized recommendation technology is applied, which collaborative filtering one core technologies while algorithm still problems. research and analysis algorithm, paper improves for problems low accuracy that considers user interest changes. It attribute scoring. uses multiattribute score item calculate user’s overall evaluation each item; change interest, time function based on Ebbinghaus forgetting law introduced similarity. given certain weight, is, function, ultimately ensure recommendation. Exploring destination marketing model can enrich relevant theories it hand, other lay foundation building real website.