Abstractive summarization of long documents using deep learning
US11170158B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 8, 2018 |
| Grant date | Nov 9, 2021 |
| Priority date | — |
| Expiry date | Sep 26, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques are disclosed for abstractive summarization process for summarizing documents, including long documents. A document is encoded using an encoder-decoder architecture with attentive decoding. In particular, an encoder for modeling documents generates both word-level and section-level representations of a document. A discourse-aware decoder then captures the information flow from all discourse sections of a document. In order to extend the robustness of the generated summarization, a neural attention mechanism considers both word-level as well as section-level representations of a document. The neural attention mechanism may utilize a set of weights that are applied to the word-level representations and section-level representations.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.