Intelligent Recommendation Scheme of Scenic Spots Based on Association Rule Mining Algorithm

This paper analyzes the development status of intelligent tourist guide system and studies Apriori-based association rule algorithm with corresponding improvement. Then this paper puts forward a weighted association rule algorithm. The algorithm comprehensively takes in to account nature, behavior and situation of tourists, to put forward three aspects of improvement in defects of efficiency and accuracy according to Apriori algorithm and it further establishes the improved tourists' behavior-preference model. On this basis, we construct personalized tourists' area recommendation model, and analyzes the instance data with data mining, to verify the accuracy in recommending framework, achieving more effective personalized scenic spot recommendation strategy.