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|Title:||Arabic documents indexing and classification based on latent semantic analysis and self-organizing map||Authors:||Mokbel, Chafic
|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.
|Appears in Collections:||Department of Electrical Engineering|
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