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UBC Theses and Dissertations
Extractive summarization of long documents by combining global and local context Xiao, Wen
Abstract
In this thesis, we propose a novel neural single-document extractive summarization model for long documents, incorporating both the global context of the whole document and the local context within the current topic. We evaluate the model on two datasets of scientific papers , Pubmed and arXiv, where it outperforms previous work, both extractive and abstractive models, on ROUGE-1 and ROUGE-2 scores. We also show that, consistently with our goal, the benefits of our method become stronger as we apply it to longer documents. Besides, we also show that when the topic segment information is not explicitly provided, if we apply a pretrained topic segmentation model that splits documents into sections, our model is still competitive with state-of-the-art models.
Item Metadata
| Title |
Extractive summarization of long documents by combining global and local context
|
| Creator | |
| Publisher |
University of British Columbia
|
| Date Issued |
2019
|
| Description |
In this thesis, we propose a novel neural single-document extractive summarization
model for long documents, incorporating both the global context of the whole
document and the local context within the current topic. We evaluate the model
on two datasets of scientific papers , Pubmed and arXiv, where it outperforms previous
work, both extractive and abstractive models, on ROUGE-1 and ROUGE-2
scores. We also show that, consistently with our goal, the benefits of our method
become stronger as we apply it to longer documents. Besides, we also show that
when the topic segment information is not explicitly provided, if we apply a pretrained
topic segmentation model that splits documents into sections, our model is
still competitive with state-of-the-art models.
|
| Genre | |
| Type | |
| Language |
eng
|
| Date Available |
2019-08-20
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| Provider |
Vancouver : University of British Columbia Library
|
| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
|
| DOI |
10.14288/1.0380504
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| URI | |
| Degree | |
| Program | |
| Affiliation | |
| Degree Grantor |
University of British Columbia
|
| Graduation Date |
2019-09
|
| Campus | |
| Scholarly Level |
Graduate
|
| Rights URI | |
| Aggregated Source Repository |
DSpace
|
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International