
		<paper>
			<loc>https://jjcit.org/paper/155</loc>
			<title>A COMPARATIVE STUDY OF DIFFERENT SEARCH AND INDEXING TOOLS FOR BIG DATA</title>
			<doi>10.5455/jjcit.71-1637097759</doi>
			<authors>Ahmed Oussous,Fatima Zahra Benjelloun</authors>
			<keywords>Big data,Indexation,Search engines,Solr,ElasticSearch,Lucene</keywords>
			<citation>9</citation>
			<views>5991</views>
			<downloads>1619</downloads>
			<received_date>17-Nov.-2021</received_date>
			<revised_date>  15-Jan.-2022</revised_date>
			<accepted_date>  26-Jan.-2022</accepted_date>
			<abstract>The  exponential  growth  of  data  generated  from  the  Moroccan  court  makes  it  difficult  to  search  for  valuable 
knowledge within multiple and huge datasets. Traditional searching methods are not adapted to Big Data context. 
Indeed, handling the search of specific information on Big Data requires advanced methods and powerful search 
systems.  To  contribute  to  the  Court  Digital  Transformation  Strategy,  we  aim  to  develop  a  solution  that  will 
leverage the technological advances in this field.The project we propose consists in developing new methods and 
techniques  of  artificial  intelligence  in  order  to  automate  the  content  of  a  large  mass  of  data  produced  by  the 
jurisdictions of the Kingdom of Morocco and to design a system capable of analyzing large volumes of complex 
judicial  data.  The  aim  is  to  discover  and  explain  certain  existing  phenomena  or  to  extrapolate  new  knowledge 
from  the  information  analyzed,  to  recognize  shapes,  make  predictions  and  make  the  necessary  adjustments  if 
necessary. For that, the purpose of this first study is to investigate and examine the existing search and indexing 
technologies for Big Data. It compares the leading solutions used for information retrieval in order to choose one 
that will serve as the base for our jurisprudential search engine.</abstract>
		</paper>


