The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Natural Language for Querying Geographic Databases
|
|
Author(s): Ghada Landoulsi (National Engineering School of Tunis, Tunisia)and Khaoula Mahmoudi (National Engineering School of Tunis, Tunisia)
Copyright: 2021
Pages: 34
Source title:
Interdisciplinary Approaches to Spatial Optimization Issues
Source Author(s)/Editor(s): Sami Faiz (University of Tunis El Manar, Tunis, Tunisia)and Soumaya Elhosni (University of Tunis El Manar, Tunis, Tunisia)
DOI: 10.4018/978-1-7998-1954-7.ch009
Purchase
|
Abstract
The amount of spatio-temporal data is growing as is its potential in improving several fields (such as hazard characterization and human diseases). Meanwhile, several problems have risen and concern specially retrieving, storing, and interpreting spatio-temporal phenomena. In fact, there is a need today to make the exploitation of this flood of information popularized for a wide range of users. Although this is not the case since now, generally managing such data requires specific skills, especially the structured query language (SQL) expertise. To profit a wide range of users from this technology, natural language is to be exploited to bridge the gap between non-expert users and geographic data exploitation. This is the scope of the chapter.
Related Content
|
Salwa Saidi, Anis Ghattassi, Samar Zaggouri, Ahmed Ezzine.
© 2021.
19 pages.
|
|
Mehmet Sevkli, Abdullah S. Karaman, Yusuf Ziya Unal, Muheeb Babajide Kotun.
© 2021.
29 pages.
|
|
Soumaya Elhosni, Sami Faiz.
© 2021.
13 pages.
|
|
Symphorien Monsia, Sami Faiz.
© 2021.
20 pages.
|
|
Sana Rekik.
© 2021.
9 pages.
|
|
Oumayma Bounouh, Houcine Essid, Imed Riadh Farah.
© 2021.
14 pages.
|
|
Mustapha Mimouni, Nabil Ben Khatra, Amjed Hadj Tayeb, Sami Faiz.
© 2021.
18 pages.
|
|
|