Unified search and return algorithm (USRA) for enhanced high utility pattern mining

Abstract

As data scales in size and complexity, traditional algorithms for pattern mining face challenges in efficiently managing both searches and return operations. This paper introduces the Unified Search and Return Algorithm (USRA), a novel approach that integrates both functionalities into a cohesive framework. By leveraging hybrid data structures and dynamic pruning techniques, USRA achieves significant improvements in runtime and memory efficiency. The proposed algorithm is evaluated against state-of-the-art methods on real-world and synthetic datasets, demonstrating superior performance in terms of scalability and resource utilization. These results establish USRA as a robust solution for high utility pattern mining in dynamic databases.