TY - JOUR
T1 - Automatic slide generation for scientific papers
AU - Sefid, Athar
AU - Wu, Jian
AU - Mitra, Prasenjit
AU - Giles, C. Lee
N1 - Funding Information:
The National Science Foundation is gratefully acknowledged for partial support.
Publisher Copyright:
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
PY - 2019
Y1 - 2019
N2 - We describe our approach for automatically generating presentation slides for scientific papers using deep neural networks. Such slides can help authors have a starting point for their slide generation process. Extractive summarization techniques are applied to rank and select important sentences from the original document. Previous work identified important sentences based only on a limited number of features that were extracted from the position and structure of sentences in the paper. Our method extends previous work by (1) extracting a more comprehensive list of surface features, (2) considering semantic or meaning of the sentence, and (3) using context around the current sentence to rank the sentences. Once, the sentences are ranked, salient sentences are selected using Integer Linear Programming (ILP). Our results show the efficacy of our model for summarization and the slide generation task.
AB - We describe our approach for automatically generating presentation slides for scientific papers using deep neural networks. Such slides can help authors have a starting point for their slide generation process. Extractive summarization techniques are applied to rank and select important sentences from the original document. Previous work identified important sentences based only on a limited number of features that were extracted from the position and structure of sentences in the paper. Our method extends previous work by (1) extracting a more comprehensive list of surface features, (2) considering semantic or meaning of the sentence, and (3) using context around the current sentence to rank the sentences. Once, the sentences are ranked, salient sentences are selected using Integer Linear Programming (ILP). Our results show the efficacy of our model for summarization and the slide generation task.
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M3 - Conference article
AN - SCOPUS:85077815060
SN - 1613-0073
VL - 2526
SP - 11
EP - 16
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
T2 - 3rd International Workshop on Capturing Scientific Knowledge, SciKnow 2019
Y2 - 19 November 2019
ER -