Currently, with the exponential rising quantity of automated textual data available on the Web, end users require the ability to get information in summary form, while keeping the most vital information in the document. As a result of this, the necessity for the creation of Summarization systems became vital. Summarization systems, collect and focus on the most important ideas of the papers and help the users to find and understand the main ideas of the text faster and in a simpler way from the dispensation of information. Compelling set of such systems are those that create summaries of extracts. This type of summary, which is called Extractive Summarization, extracts the most applicable sentences from the main document. The used methods, usually assign a score for every sentence in the text, based on specific features. Then choose the most important sentences, according to the degree of score for each sentence. Nevertheless, not have been achieved quality summaries corresponds with t