Research on Mining Methods of User Behavior Patterns in Smart Home
Wen Sun · 2022
To realize the user interaction of smart home, this paper focuses on the cluster analysis and association analysis technology, which is used to mine the control habits of smart home users, and proposes a mining and home appliance control strategy based on user behavior pattern. The algorithm mines frequent itemsets from user behavior data, evaluates it with association rules and obtains strong positive correlation association rules. Then it analyzes the association of user behavior in different time periods by using temporal association rule technology, uses hierarchical clustering method to analyze user behavior data, and obtains similar usage patterns between household appliances. Finally, according to the above-mentioned user behavior habits, the intelligent control design of household appliances is performed. The experimental results show that the association rule data mining method can predict the future behavior of users in smart home environment, and the Apriori algorithm based on hash technology can improve the efficiency of user behavior prediction in smart home.