Authors:
Eric Kergosien
1
;
Hugo Alatrista-Salas
2
;
Mauro Gaio
3
;
Fabio Güttler
4
;
Mathieu Roche
5
and
Maguelonne Teisseire
5
Affiliations:
1
Univ. Lille, France
;
2
Pontificia Universidad Católica del Perú, Peru
;
3
Univ. Pau, France
;
4
Univ. Strasbourg, France
;
5
UMR TETIS & LIRMM, France
Keyword(s):
Natural Language Processing, Information Retrieval, Spatial Information, Land-use Planning.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Analytics
;
Context Discovery
;
Data Analytics
;
Data Engineering
;
Information Extraction
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Mining Text and Semi-Structured Data
;
Symbolic Systems
;
Visual Data Mining and Data Visualization
Abstract:
With the amount of textual data available on the web, new methodologies of knowledge extraction domain are provided. Some original methods allow the users to combine different types of data in order to extract relevant information. In this context, we present the cornerstone of manipulations on textual documents and their preparation for extracting compatible spatial information with those contained in satellite images. The term footprint is defined and its extraction is performed. In this paper, we describe the general process and some experiments conducted in the XXX project, which aims to match the information coming from texts with those of satellite images.