A New Algorithm for Term Weighting in Text Summarization Process

The importance of good weighting methodology in information retrieval methods – the method that affects the most useful features of a document or query representative is examined. Good weighting methodologies are supposed to be more important than the feature selection process. Weighting features is the thing that many information retrieval systems are regarding as being of minor importance as compared to find the features; but the experiments suggest that weighting is noticeably more important than feature selection. There are different methods for the term weighting such as TF*IDF and Information Gain Ratio which have been used in information retrieval systems. In this paper we aim to explore a new algorithm for using GA in term weighting for text summarization process and then by deploying it as an appropriate developed prototype, the outcomes are analyzed and some conclusions for Information Retrieval are considered.