01756nas a2200205   4500000000100000000000100001008004100002260001200043653002300055653002300078653001000101100002400111700002100135245009200156856009800248300001000346490000600356520117400362022001401536       2014                            d  c06/201410aGenetic Algorithms10aRule Based Scripts10aEzafe1 aMehrnoush Shamsfard1 aSamira Noferesti00aA Hybrid Algorithm for Recognizing the Position of Ezafe Constructions in Persian Texts  uhttp://www.ijimai.org/journal/sites/default/files/files/2014/03/ijimai20142_6_2_pdf_23890.pdf  a17-250 v23 aIn the Persian language, an Ezafe construction is a linking element which joins the head of a phrase to its modifiers. The Ezafe in its simplest form is pronounced as –e, but generally not indicated in writing. Determining the position of an Ezafe is advantageous for disambiguating the boundary of the syntactic phrases which is a fundamental task in most natural language processing applications. This paper introduces a framework for combining  genetic algorithms with rule-based models that brings the advantages of both approaches and overcomes their problems. This framework was used for recognizing the position of Ezafe constructions in Persian written texts. At the first stage, the rule-based model was applied to tag some tokens of an input sentence. Then, in the second stage, the search capabilities of the genetic algorithm were used to assign the Ezafe tag to untagged tokens using the previously captured training information. The proposed framework was evaluated on Peykareh corpus and it achieved 95.26 percent accuracy. Test results show that this proposed approach outperformed other approaches for recognizing the position of Ezafe constructions.  a1989-1660