Ranking of keyword-combined searches in relational databases based on relevance to the user query

W.-K. Loh; H.-Y. Kwon

Ranking of keyword-combined searches in relational databases based on relevance to the user query

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Author(s): W.-K. Loh¹ and H.-Y. Kwon²
- Affiliations: 1: Department of Software , Gachon University , Seongnam 13120 , Republic of Korea ;
  2: Department of Industrial and Systems Engineering , Seoul National University of Science and Technology , Seoul 01811 , Republic of Korea
Source: Volume 56, Issue 10, 14 May 2020, p. 495 – 498
DOI: 10.1049/el.2019.4266 , Print ISSN 0013-5194, Online ISSN 1350-911X

Received 31/12/2019, Published 27/02/2020

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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Ranking of keyword-combined searches in relational databases based on relevance to the user query

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