Open AccessRanking of keyword‐combined searches in relational databases based on relevance to the user query
Author(s) -
Loh W.K.,
Kwon H.Y.
Publication year - 2020
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2019.4266
Subject(s) - relevance (law) , ranking (information retrieval) , information retrieval , computer science , keyword search , relational database , database , query expansion , law , political science
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.