This paper describes Automatic Caption generation for news Articles, it is an experimental intelligent system that generates presentations in text based on the text knowledge power series representation model. Captions or titles are useful for users who only need information on the main topics of an article. Using current extractive summarization techniques, it is not able to generate a coherent document summary shorter than a single opinion, or to produce a brief that conforms to specific linguistic constraints. The power series representation (PSR) model, which has a low complex computation in text knowledge constructing process. This model can provide rich knowledge and automatic construction. Our model experience to design captions from a database of news articles, and from the associated images in them, and their captions, and consists of two stages. Text assertions is that the keywords/terms that stand for the common knowledge and Text association rules, are referred to these term's relations that are causations and reflect the semantic relationships in a text. It is viable to generate captions from the news by mapping the PSR and the image associated with the news article.

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