@ARTICLE{10.21494/ISTE.OP.2020.0489, 

TITLE={Combinations of statistical and semantic approaches applied to scientific digital libraries for the promotion of multidisciplinary research}, 
  
AUTHOR={Fabrice Muhlenbach, Hussein T. Al-Natsheh, }, 
	
JOURNAL={Open Journal in Information Systems Engineering}, 
	
VOLUME={1}, 

NUMBER={Issue 1}, 
	
YEAR={2020}, 

URL={https://openscience.fr/Combinations-of-statistical-and-semantic-approaches-applied-to-scientific}, 
	
DOI={10.21494/ISTE.OP.2020.0489}, 
	
ISSN={2634-1468}, 
	
ABSTRACT={The knowledge of all science domains is now available on digital libraries. The problem is that the papers belonging to different research communities do not use the same vocabulary to talk about the same subject. Access to relevant documents with information retrieval tools, search engines or research-paper recommender systems will fail if these methods do not consider this linguistic variability. In this work, we present strategies for using artificial intelligence technologies to successfully expand the literature search to bring diversity to the recommended results, thereby promoting multidisciplinary research.}}