Arabic Stemmer Based Big Data
By its morphological and syntactic richness, the Arabic language is considered among the most difficult languages to deal with it in the field of information search. This is due; in particular, to the various difficulties encountered in its Stemming, which has not yet experienced a standard approach. The Stemming algorithm for Arabic words has been an important topic in Arabic information retrieval. The intention of this article is to parallelize a stemming algorithm for Arabic by proposing a distributed stemming algorithm in a big data system. This is by using the Hadoop framework, the MapReduce programming model for the development of the algorithm, and the distributed file system HDFS for the Storage of stemming result.
Year of publication: |
2018
|
---|---|
Authors: | Madani, Youness ; Erritali, Mohammed ; Bengourram, Jamaa |
Published in: |
Journal of Electronic Commerce in Organizations (JECO). - IGI Global, ISSN 1539-2929, ZDB-ID 2115949-X. - Vol. 16.2018, 1 (01.01.), p. 17-28
|
Publisher: |
IGI Global |
Subject: | Arabic Language | Big Data | Distributed Stemming | Hadoop | HDFS | MapReduce | Stemming Algorithm |
Saved in:
Saved in favorites
Similar items by subject
-
Madani, Youness, (2018)
-
Towards a New Model of Storage and Access to Data in Big Data and Cloud Computing
Matallah, Houcine, (2017)
-
Performance Evaluating System Based on MapReduce in Context of Educational Big Data
Verma, Chitresh, (2018)
- More ...
Similar items by person
-
Madani, Youness, (2018)
- More ...