Title :
Indexing evidential data
Author :
Jammali, Anouar ; Tobji, Mohamed Anis Bach ; Martin, Arnaud ; Ben Yaghlane, Boutheina
Author_Institution :
LARODEC, Univ. of Tunis, Tunis, Tunisia
Abstract :
Querying imperfect data received increasing attention in the area of database management. The complexity and the volume of imperfect data requires advanced techniques for efficient access, and satisfying user-queries in a reasonable response time. In this paper, we are particularly interested in evidential databases, i.e., databases where imperfection is represented through Dempster-Shafer theory. To answer user-queries in such databases, we propose a new index system based on a tree data structure (e-Tree) that is adapted to the complexity of the evidential data. The experiments done on our solution showed encouraging results.
Keywords :
data handling; indexing; inference mechanisms; query processing; tree data structures; uncertainty handling; Dempster-Shafer theory; database management; evidential data complexity; evidential data indexing; imperfect data complexity; imperfect data querying; imperfect data volume; tree data structure; Cancer; Diseases; Indexing; Dempster-Shafer theory; evidential database; indexing data;
Conference_Titel :
Complex Systems (WCCS), 2014 Second World Conference on
Print_ISBN :
978-1-4799-4648-8
DOI :
10.1109/ICoCS.2014.7060942