Extractive Text Summarization Techniques of News Articles: Issues, Challenges and Approaches

With the burst of information on the Web, there is a need to compress without eliminating facts and index for further reference highlighting the need for automatic text summarization techniques. With the increasing social and occupational requisites, humans need to process large amounts of information to obtain key points in a short period of time. The paper reviews various web extraction technologies available to obtain real-time data necessary for new like articles. The paper goes on to describe various automatic text summarization techniques and their inherent mechanisms in pruning text logically. In further evaluation, summarizers' performances are tested against manually generated summaries using ROGUE parameters. The web extractors are analyzed based on subjective time and space efficiency. The basic understanding of web extraction and summary generation is noted, the requirements are outlined and the proposed parameters are presented as a conclusion of the review presented.