Abstract
A novel technique is introduced for verb and inflection detection in Persian texts. This recognition can be useful for preprocessing phase in natural language processing (NLP) and text mining like partof-speech (POS) tagging and sentence boundary detection (SBD) in Persian texts. Our technique employs structural information of Persian verb for the first phase of this detection and then uses the n-gram approach for Homograph Disambiguation in order to increase the performance as the second phase. Experimental results show that our technique can achieve high efficiency performance (99%) which is an exemplar solution for Persian SDB and POS tagging problem domain.
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