Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/391
Title: Arabic documents indexing and classification based on latent semantic analysis and self-organizing map
Authors: Mokbel, Chafic 
Greige, Hanna 
Sarraf, Charles
Kurimo, Mikko
Affiliations: Department of Electrical Engineering 
Department of Mathematics 
Issue Date: 2001
Part of: Proceedings of the IEEE workshop on Natural Language Processing in Arabic
Conference: Workshop on Natural Language Processing in Arabic (2001 : Beirut, Lebanon) 
Abstract: 
This paper describes an Arabic document indexing system based on a hybrid "Latent Semantic Analysis"(LSA) and "Self-Organizing Maps"(SOM) algorithm. The approach has the advantage to be completely statistic and to automatically infere the indices from the documents database. A rule-based stemming method is also proposed for the Arabic language. The whole system has been experimented on a database formed of the Alnahar newspaper articles for 1999. Documents clustering and few experiments in retrieval have provided satisfactory results.
URI: https://scholarhub.balamand.edu.lb/handle/uob/391
Type: Conference Paper
Appears in Collections:Department of Electrical Engineering

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