TOURISM ROUTE ASSOCIATION RECOMMENDATION ALGORITHM BASED ON CHANGES IN USER'S INTEREST CHARACTERISTICS

In order to improve the ability to recommend tourism routes and increase tourist route satisfaction. This article designs a tourism route association recommendation algorithm based on changes in user interest characteristics. This article provides information on the distribution of tourist routes and Constructs the topology structure of tourism routes. The paper utilizes a multi-block fusion matching method to construct an optimal feature allocation model, Using optimized spatial clustering fuzzy functions to mine preference feature models and Introducing a joint distribution density function to solve the correlation recommendation of tourist routes. The experimental results show that when using this algorithm, the accuracy of the sample set is improved by 1.6% compared to the accuracy of the test set, and the recall rate is improved by 2.9%. Compared with the traditional algorithm, the proposed algorithm has the highest confidence and the best regression effect, which indicates that the proposed algorithm can effectively improve the recommendation efficiency.