Generating a topic-based summary of textual content
US10685050B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 23, 2018 |
| Grant date | Jun 16, 2020 |
| Priority date | — |
| Expiry date | Sep 14, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A word generation model obtains textual content and a requested topic of interest, and generates a targeted summary of the textual content tuned to the topic of interest. To do so, a topic-aware encoding model encodes the textual content with a topic label corresponding to the topic of interest to generate topic-aware encoded text. A word generation model selects a next word for the topic-based summary from the topic-aware encoded text. The word generation model is trained to generate topic-based summaries using machine learning on training data including a multitude of documents, a respective summary of each document, and a respective topic of each summary. Feedback of the selected next word is provided to the word generation model. The feedback causes the word generation model to select subsequent words for the topic-based summary based on the feedback of the next selected word.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.