Particle Swarm Optimization-Based Association Rule Mining in Big Data Environment

Abstract

With the explosive growth of information data in today's society, the continuous accumulation and increase of data in recent years make it difficult to extract useful information from it, so data mining comes into being. Association rule mining is an important part of data mining technology. Association rule mining is the discovery of frequent item sets in a large amount of data and the mining of strong association relations between them. Traditional association rule algorithms need to set minimum support and minimum confidence in advance. However, these two values are largely influenced by human subjectivity. Many scholars use average and weight to set these two values, but the effect is still not very good. In order to solve this problem, this paper proposed an improved algorithm of association rules-PSOFP growth algorithm, this algorithm is introduced into intelligent algorithm, particle swarm optimization algorithm, it can find the global optimal solution, we use this fact to find the optimal support, then using FP-growth algorithm for mining association rules, and finally put forward by information entropy to measure effectiveness in association rules mining, and the improved algorithm was applied to the social security event correlation analysis, the improved algorithm proved to our expectations.

A Novel Association Rule Mining Model for Generating Positive and Negative Association Rules with Hybridized Meta-Heuristic Development

“…In 2019, Su et al [24] have incorporated the heuristic technique along with the ARM for mining and generating both negative and positive rules using FP-growth and particle swarm optimization (PSO). This optimizer has discovered the optimal solutions and discovered global support, where the association rules were mined using the FP-growth technique.…”

“…• Due to large datasets and large block sizes, structural complexity occurs. Suet al [24] PSO • Enhances the efficiency of the model and evades the artificial blind setting.…”

“…datasets and blocks, structural complexity occurs. PSO [24] enhances the efficiency of the model and evades the artificial blind setting. It is suggested to include the hybridized algorithm for further enhancement.…”

A Recommendation Model for Selling Rules in the Telecom Retail Industry

“…Consequently, the question of how to extract effective and meaningful knowledge from these historical data has become an important research topic. In recent years, the most commonly used analysis method for big data involves applying data mining-related approaches to extract features and patterns from huge datasets [1][2][3] so as to obtain meaningful or valuable information.…”

Feasibility Analysis Model of Transformation from Real Economy to Virtual Economy Based on Association Rule Algorithm

“…In addition to some unexpected conclusions, data mining can also predict and analyze customers' interests and purchasing tendencies through historical data of customers, to achieve effective product push. If a customer purchases a book on Taobao, Taobao will push similar books again, thereby increasing the possibility of commodity transactions [5,6]. e association rule algorithm can express the dependency and the degree of correlation between a certain event and other events.…”