News channels established a 24-hour news habit which gets updated virtually in every second. Archiving becomes a challenging process since the news production is huge. Viewers are interested in news stories as it delivers useful and detailed information in short form. The news story created based on the history and the latest news updates The journalists access news archives to get details about the news happened related to the new happenings. Searching archives, fetching and linking related news is a tedious job for a reporter. In this work, a system is suggested which uses ontology and vanilla recurrent neural network to create news automatically for a query. The framework is evaluated using BLEU method and correlated with human evaluation. Ontology completeness decides the quality of the news generated.

Ontology, Deep learning, recurrent neural network, news generation, Personalization

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