@ARTICLE{10.21494/ISTE.OP.2019.0334, 

TITLE={Harness the hetorogeneity in textual data}, 
  
AUTHOR={Jacques Fize, Mathieu Roche, Maguelonne Teisseire, }, 
	
JOURNAL={Information Retrieval, Document and Semantic Web}, 
	
VOLUME={2}, 

NUMBER={Issue 1}, 
	
YEAR={2019}, 

URL={https://openscience.fr/Harness-the-hetorogeneity-in-textual-data}, 
	
DOI={10.21494/ISTE.OP.2019.0334}, 
	
ISSN={2516-3280}, 
	
ABSTRACT={Over the last decades, there has been an increasing use of information systems, resulting in an exponential increase in textual data. Although the volumetric dimension of these textual data has been resolved, its heterogeneous dimension remains a challenge for the scientific community. The management of the heterogeneity in data offers many opportunities through an access to a richer information. In our work, we design a process for mapping heterogeneous textual data, based on their spatiality. In this article, we present the results returned by this process on data produced in Madagascar as part of the BVLAC project, led by CIRAD. Based on a set of 4 quality criteria, we obtain good spatial correspondence between these documents.}}