NEWS SUMMARY GENERATION FRAMEWORK BASED ON ONTOLOGY AND NATURAL LANGUAGE PROCESSING TECHNIQUES

News archiving becomes a formidable task due to the perpetual generation of news. Archives play a vital role in crafting personalized news programs. Adhering patches of information, crafting the story and shaping up a news script defines the whole process of news generation. Creating refreshed news stories in small time intervals perch in as a challenge. The journalists access news archives to procure details about the past events related to the latest news update. The whopping amount of news articles which pops out on a single query makes extracting the relevant information a tedious task for the news reporter. Here we present news summary generation system based on ontology and natural language processing techniques. The system is tested using BLEU method and correlated the metric score with human evaluation.