Presentation slides generation from scientific papers using support vector regression

As the presentation slides are of vital importance in a person's career, a significant amount of time is spent for its preparation. An automatic paper-summarizer will reduce the amount of time and human effort. Presently, tools exist for formatting and designing themes for slides, but not for content generation. This paper proposes a summarization system that automatically generates presentation slides from scientific papers. The proposed system accepts scientific papers as input and prepares presentation slides, which includes text, images and graphs present in them. Papers and slides are learned and trained using Support Vector Regression model. It calculates and predicts the regression scores. Based on the regression scores, the relevant content of the paper is selected for generating summary. The generated summary is used for making slides using Integer Linear Programming along with the images present in papers.