Extractive text Summarization using Genetic Clustering Algorithm

Abstract: Text summarisation is largely summarizing the source text into a simplified short version maintaining its actual information content and also the abstract that means. Attributable to apace growing use of internet, the globe is additionally facing drawback to tackle with dangerous quantity of data often facet by facet in kind of text .The bountiful offer of data generally cause time delay within the search of information recovery. In this relative concern automatic text summarisation has a crucial issue concerning data recovery of time. Manually summarizing giant document of text is incredibly troublesome task for individual. For this, extractive summarizing tool supported verified algorithm is required. Therefore supported the analysis of already planned model of extractive text summarisation, We are developing extractive text summarization tool based on genetic algorithm named AETS.. This approach are valid victimization normal information sets and quality measures.

Keywords: Feature extraction, Text summarization, Part of speech, Automatic text, Semantic nets.