Natural Language Processing based Soft Computing Techniques
نویسنده
چکیده
This paper presents the implementation of soft computing (SC) techniques in the field of natural language processing. An attempt is made to design and implement an automatic tagger that extract a free text and then tag it. The part of speech taggers (POS) is the process of categorization words based on their meaning, functions and types (noun, verb, adjective, etc). Two stages tagging system based MPL, FRNN and SVM are implemented and designed. The system helps to classify words and assign the correct POS for each of them. The taggers are tested using two different languages (Arabic and Hindi). The Word disambiguation issue has been solved successfully for Arabic text. Experience has shown that the proposed taggers achieved a great accuracy (99%).
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