A method to generate text summary by accounting pronoun frequency for keywords weightage computation

In recent years large volume of data being generated every day from various sources. Text summarization has become more relevance for quick searching, abstract generating, automatic sorting etc., to larger volume of data. Extractive methods are involved in identifying important part of the text to produce summary. While generating the summary by extractive methods, important keywords are identified by eliminating stopwords. As a part of stopwords removal, pronouns which are used as placeholders for proper nouns in text are usually removed. But frequency information related to pronouns is significant to improve the quality of summary being generated. We propose in this research a method to replace pronouns with their corresponding proper nouns and then compute the frequency of keywords. The keywords weightage has been calculated based on frequency which intern used to extract important sentences to form the summary. Experiments are conducted on text data collection and a gain ratio is computed to measure improvement in summary generated from pronoun replacement method.