Abstract
This paper studied the application of computer aided design in tourism planning. In this paper, the recommendation system of hybrid travel recommendation based on hybrid collaborative filtering was a personalized recommendation system designed for tourism market. Combining the two basic algorithms, through constant analysis and experiment, the algorithm was improved by optimizing the recommendation degree to improve the coverage. The interest of users and items was balanced, adding heat and Raiders city heat parameters. This paper calculated the recommended degrees based on the travel users, travel strategies and tourist cities, and then balanced the three degrees of recommendation to get the final degree of recommendation, which greatly increased the coverage of the recommended strategy and solved the “long-tail effect” recommendation problem.
Published Version
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