Document Type

Conference Paper

Publication Date

2019

Publication Title

CEUR Workshop Proceedings- Proceedings of the Third International Workshop on Capturing Scientific Knowledge co-located with the 10th International Conference on Knowledge Capture (K-CAP 2019)

Pages

1-6

Conference Name

SciKnow 2019- Third International Workshop on Capturing Scientific Knowledge co-located with the 10th International Conference on Knowledge Capture (K-CAP 2019), November 19, 2019, Marina del Ray, California

Abstract

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.

Comments

Link to conference website: https://ceur-ws.org/Vol-2526/

Rights

© 2019 for this paper by its authors.

Use permitted under a Creative Commons Attribution 4.0 International (CC BY 4.0) License.

Original Publication Citation

Sefid, A., Wu, J., Mitra, P., & Giles, C. L. (2019) Automatic slide generation for scientific papers. CEUR Workshop Proceedings- Proceedings of the Third International Workshop on Capturing Scientific Knowledge co-located with the 10th International Conference on Knowledge Capture (K-CAP 2019), 2526, (11-16). https://par.nsf.gov/servlets/purl/10173903

ORCID

0000-0003-0173-4463 (Wu)

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