Research Article
Updating Relational Databases with Linguistic Data Based on Hedge Algebras
366 downloads
@INPROCEEDINGS{10.1007/978-3-319-15392-6_27, author={Le Hung and Vu Loc and Hoang Tung}, title={Updating Relational Databases with Linguistic Data Based on Hedge Algebras}, proceedings={Nature of Computation and Communication. International Conference, ICTCC 2014, Ho Chi Minh City, Vietnam, November 24-25, 2014, Revised Selected Papers}, proceedings_a={ICTCC}, year={2015}, month={2}, keywords={Hedge algebras Relational databases with linguistic data Semantically quantifying mapping Similarity relation of depth k Clear key Mixture key Fuzzy key}, doi={10.1007/978-3-319-15392-6_27} }- Le Hung
Vu Loc
Hoang Tung
Year: 2015
Updating Relational Databases with Linguistic Data Based on Hedge Algebras
ICTCC
ICST
DOI: 10.1007/978-3-319-15392-6_27
Abstract
Relational Databases (DB) with linguistic data based on hedge algebras (HA) were introduced, following this approach, data manipulation (include linguistic data) is simpler and more efficient, practical than the other one. On this basis, in this paper, we will present the update operations on relational databases with linguistic data based on HA. Update operations are built by mean of semantically quantifying mapping (SQM) and similarity relation of depth k, where k is the length of a linguistic value that belongs to the values domain of an attribute.
Copyright © 2014–2024 ICST