An Emerging Standard Miniaturization in Arabic Morphological Analysis

Currently, the topic of natural language processing, morphological analysis, is a new emerging topics in the world. The main idea of morphological analysis may allow the identification of the literal origin of two words either root or seed and achieve the comparison to the original word. This paper describes a new idea related to standard miniaturization approach for Arabic morphological analysis. This approach based on regular noun morphological automaton technique (RNMT). The proposed algorithm focuses on a morphological regular abstractive noun (singular masculine) with length 3, 4 and 5 letters, which in turn, produce a special type of morphological miniaturization that is based on the concept of world analysis and restructure according to morphine scales. This aspect contribute to develop the Arabic morphological miniaturization, by developing the standardization aspect. It can be exploited by NLP applications like syntactic and semantic analysis, information retrieval, machine translation and orthographical correction. The result reveals that the proposed algorithm is anew attempt in Arabic language) Morphological analysis) and it is perfectly work on research sample, however, doesn't recognize between the enter words if it noun or verb.