Resolving Inflected Text Structures Irregularities Using Rule-Based Models

Abstract

In this paper a model, for natural language inflected irregular text structure, is developed in order to automatically be able to derive stems from given text words. The proposed system is modeled in away so that it has the ability to act in two ways forward and backword which is called bi-directional Techniques. It can deduce morphemes from inflected words and, at the same time, can build inflected words from stems.  The proposed system is developed and built using first-order logic techniques.The Proposed rule-based model will help researchers to do more investigation and works on multiligual applications that help facilitate many applications in our real life. Those applications can cover topics ranging from  medical diagnosis systems,  machine translation,…, to e-government entities through teaching expository text structure to facilitate reading comprehension. The proposed model be able learn how to extract rules from information by applying logic programming techniques to natural language data.

Keywords:syntax Analysis, Irregular plurals, rule-based, bi-directional, Inflected words, stems, finite atomaton