Sentence Reduction based on Automatic Document Text Summarization and Crossbred Framework

Recently, the growth of technology has resulted in a rise in text data acquired from a variety of sources and anticipated to attract substantial growth and attention. The enormous quantity of textual content renders manual text summarization infeasible due to the time, effort, and expense required. Extraction of actionable insights from text data is vital because it provides organizations and users with solutions that increase their value. Since the 1950s, academics have endeavored to enhance ATS techniques. The people are projected to compile summaries based on summary type. Therefore, Automatic Text Summarization (ATS) is the reduction of a large quantity of information into a concise and easily understood summary and useful others. The subject matter and meaning of the text must be preserved during using the ATS. Based on the above summary, a new automatic text summarization system has been suggested based on the crossbred framework. The suggested work consists of different phases. begin with preprocessed and conclude with the classification phase. The performance results provide better results for suggested classification based on the different evaluations.