Automatic extraction of important words from important parts of the Aeronautical scientific papers with a Standard structure

One of the applications of artificial intelligence, that can be pointed, is the system automation. Like other automatic text processing systems, concerns of exploring and text processing that can be pointed out are: find words, important phrases and parts, structure, morphology, ontology, and the relationship between words. Hence, a mechanism to find important parts, and explore key words in important parts will be presented. Since most existing methods are complicated, involved mathematical and statistical relationships, so to reduce the complexity and increase the speed of processing, the structures of aeronautical scientific articles have been used. So this structure can used to extract the most useful parts. And considering that the most important parts are the important words, therefore these words are explored based on rank and status in the text and in the important parts of the main text. Important words are used for summarizing goals, machine translation and other natural language processing applications and text search.

Keywords:

text structure , important parts , Aeronautical key words , ratings , word count