Internet of Things Massive Data Analysis System Based on Association Rules Algorithm

With the vigorous development of the social economy and the continuous improvement of the level of science and technology, people's requirements for the quality of life are gradually improving. Internet of Things technology, as a rapidly developing field, has also made great progress. Based on the existing data mining methods, this paper presents a network retrieval algorithm based on association rules. The characteristics of the algorithm include simple, practical and easy to maintain operation, which can provide timely, accurate and reliable information for decision makers, and has good scalability and visualization degree. In this paper, the association rules algorithm is used to design the massive data analysis system of the Internet of Things, and the performance of the system is tested and studied. The test results show that every time the data size increases by 10 times, the data processing time also increases, showing an approximate linear relationship. In the mass data analysis system, processing larger data will lead to longer processing time, that is, the data processing time is proportional to the data scale. By meeting user needs, improving system performance and reducing cost, the algorithm can effectively use resources.