Efficient Top-k Keyword Search in Relational Databases Considering Integrated Candidate Network
Fatemeh Khalifeh, Mohammad Taheri, Seyed Mostafa Fakhrahmad, Eghbal G. Mansoori · IEEE Access · 2024
Efficiently navigating vast datasets without requiring query language expertise is crucial in the era of Big Data. Keyword search in relational databases offers a promising solution, but many existing methods struggle with datasets of moderate size, such as one million tuples. This paper introduces a novel approach using an Integrated Candidate Network (ICN) to enhance query responses by reducing redundant operations and pruning non-promising candidate networks. Unlike approaches focusing on Large Language Models (LLMs) for unstructured data, our method uniquely optimizes structured data environments. Experimental evaluations across diverse real-world databases demonstrate significant enhancements in query efficiency and effectiveness. This research contributes to advancing keyword search in relational databases by leveraging structured data principles to address current limitations.