Data Evaluation System Utilizing Logic-Based Rules
Naveen Koka · Journal of Artificial Intelligence Machine Learning and Data Science · 2023
In modern software systems, the dynamic generation of queries plays a crucial role in retrieving relevant data based on userdefined criteria.This paper explores a runtime approach where criteria names are utilized to dynamically construct queries tailored to specific system contexts.The generated queries vary depending on the requirements of the system, ensuring the retrieval of data that meets the specified criteria.Furthermore, to enhance performance and optimize resource utilization, the paper proposes a caching mechanism for storing generated queries.Once a query is generated, it is cached to eliminate the need for repeated evaluation, thereby reducing overhead and improving response times.This caching strategy ensures that subsequent data retrieval operations can be executed efficiently, contributing to a more responsive and scalable system architecture.Overall, this paper presents a dynamic query generation and caching framework that facilitates efficient data retrieval in diverse system environments.By leveraging runtime query generation and caching, software systems can achieve enhanced performance and responsiveness, ultimately improving user experience and system scalability.