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Headline Generation using Deep Neural Networks
In: Master's Projects (2017)
Abstract: News headline generation is one of the important text summarization tasks. Human generated news headlines are generally intended to catch the eye rather than provide useful information. There have been many approaches to generate meaningful headlines by either using neural networks or using linguistic features. In this report, we are proposing a novel approach based on integrating Hedge Trimmer, which is a grammar based extractive summarization system with a deep neural network abstractive summarization system to generate meaningful headlines. We analyze the results against current recurrent neural network based headline generation system.
Keyword: Artificial Intelligence and Robotics; Databases and Information Systems; Headline Generation; Neural Nets; Text Summarization
URL: https://scholarworks.sjsu.edu/cgi/viewcontent.cgi?article=1526&context=etd_projects
https://scholarworks.sjsu.edu/etd_projects/526
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