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Ranking of keyword-combined searches in relational databases based on relevance to the user query
- Authors
- Loh, W. -K.; Kwon, H. -Y.
- Issue Date
- May-2020
- Publisher
- INST ENGINEERING TECHNOLOGY-IET
- Keywords
- relational databases; query processing; relevance feedback; text analysis; keyword-combined searches; relational databases; KEYSIM searches; threshold-based method; user query relevance; top-k results; numerical similarity; textual similarity
- Citation
- ELECTRONICS LETTERS, v.56, no.10, pp.495 - 497
- Journal Title
- ELECTRONICS LETTERS
- Volume
- 56
- Number
- 10
- Start Page
- 495
- End Page
- 497
- ISSN
- 0013-5194
- Abstract
- In this Letter, the authors deal with ranking of keyword-combined searches in relational databases based on relevance to the user query, which they call KEYSIM searches. They formally define KEYSIM searches and propose a threshold-based method for efficiently processing KEYSIM searches. Their proposed method is the first one to find top-k results considering both numerical similarity and textual similarity. Through the experiments using five real and synthetic data sets, they show the efficiency and scalability of the proposed method.
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Related Researcher
- Loh, Woong Kee
- College of IT Convergence (Department of Software)