Abstract: Aiming at the problem that the data extraction method can not carry out massive mining, the mining results are inaccurate and the mining time is long, a regional strong association rule data extraction method based on data mining algorithm is proposed. Combined with the data management system of strong regional association rules, user demand information is collected, feature relevance is retrieved, drama features are obtained. The data relevance is used to analyze the association between drama features in drama retrieval, calculate similar label information parameters, calculate the support and confidence, and mine association rules from the database of strong regional association rules. Kulczynski measure and imbalance rate is used to implement correlation
analysis and filtering, and finally the strong association rules are obtained with practical significance. The experimental results show that this method has high mining efficiency and wide application value.

Key words: data association degree； , regional and strong association rule data； , data fetch； , strong association rules