Abstract: According to the disadvantage of consuming great memory cost in storing massive data existing in the FP-Growth algorithm of mining association rules, the paper presents an improved algorithm which adds interestingness to FP-Growth, and then compares it with Apriori and FP-Growth algorithm, the improved algorithm greatly reduces the memory cost and improves the efficiency of system execution. Based on the idea of combining the improved algorithm with the tourism route planning, taking Yunnan tourism as the tourism planning object and fully applying the large data of the tourism website, the paper designs a mining system for tourism route planning, and finds out the association rules between tourist routes and scenic spots.

Key words: data mining, FP-Growth algorithm, interestingness, tourism plan, index