A COMPARATIVE STUDY OF DIFFERENT SEARCH AND INDEXING TOOLS FOR BIG DATA

Abstract

The exponential growth of data generated from the Moroccan court makes it difficult to search for valuable knowledge within multiple and huge data sets. Traditional searching methods are not adapted to Big Data context. Indeed, handling the search of specific information on Big Data requires advanced methods and a 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, to make predictions and to 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 [JJCIT 2022; 8(1.000): 72-86]

Keywords

• big data
• indexation
• search engines
• solr
• elasticsearch
• lucene