Dynamic Information Monitoring Method for Enterprise Operation Based on Apriori Algorithm

In modern enterprise operations, dynamic information monitoring plays a crucial role in guiding enterprise decision-making, optimizing operation processes and improving market competitiveness. In the business field, especially in enterprise operation, Apriori algorithm can be used to monitor and analyse dynamic information, such as customer transaction data, to discover the correlation between products, improve inventory management and product layout, and optimize overall sales strategy. Therefore, this paper proposes a dynamic information monitoring method for enterprise operation based on Apriori algorithm, which stores the data in a matrix, using 0 and 1 to indicate the existence or non-existence of data in the database. The support count of items is obtained by calculating the number of 1's in the matrix vector, which simplifies the judgement of frequent item sets. After generating a new frequent item set, it is transferred to the queue, using the first-in-first-out nature of the queue, so that the generated frequent item set is always in order, avoiding its recurrence. For the generated frequent item sets, this paper adopts the combined rule generation scheme and proposes the dynamic minimum confidence degree, which makes the association algorithm closer to the real data and therefore effectively prevents the occurrence of too many useless rules and the omission of effective rules. After the rule generation process, the concept of enhancement is incorporated to guarantee the coherence of the dynamic minimum confidence setting. This ensures that the resultant strong association rules are refined and efficient, making them applicable in practical scenarios. The experimental results show that through Apriori algorithm, companies can identify which product combinations are frequent and thus optimise their inventory management strategy. By monitoring and analyzing the operation data in real time through Apriori algorithm, enterprises can discover potential risk factors in time and take corresponding measures to cope with and prevent them.