Arabic documents indexing and classification based on latent semantic analysis and self-organizing map

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.