Text Summarization Extraction System (TSES) Using Extracted Keywords

A new technique to produce a summary of an original text investigated in this paper. The system develops many approaches to solve this problem that gave a high quality result. The model consists of four stages. The preprocess stages convert the unstructured text into structured. In first stage, the system removes the stop words, pars the text and assigning the POS (tag) for each word in the text and store the result in a table. The second stage is to extract the important keyphrases in the text by implementing a new algorithm through ranking the candidate words. The system uses the extracted keywords/keyphrases to select the important sentence. Each sentence ranked depending on many features such as the existence of the keywords/keyphrase in it, the relation between the sentence and the title by using a similarity measurement and other many features. The Third stage of the proposed system is to extract the sentences with the highest rank. The Forth stage is the filtering stage. This stage reduced the amount of the candidate sentences in the summary in order to produce a qualitative summary using KFIDF measurement.