Keyphase extraction beyond language modeling
US11657223B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 16, 2021 |
| Grant date | May 23, 2023 |
| Priority date | — |
| Expiry date | Dec 16, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L2015/088
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system for extracting a key phrase from a document includes a neural key phrase extraction model (“BLING-KPE”) having a first layer to extract a word sequence from the document, a second layer to represent each word in the word sequence by ELMo embedding, position embedding, and visual features, and a third layer to concatenate the ELMo embedding, the position embedding, and the visual features to produce hybrid word embeddings. A convolutional transformer models the hybrid word embeddings to n-gram embeddings, and a feedforward layer converts the n-gram embeddings into a probability distribution over a set of n-grams and calculates a key phrase score of each n-gram. The neural key phrase extraction model is trained on annotated data based on a labeled loss function to compute cross entropy loss of the key phrase score of each n-gram as compared with a label from the annotated dataset.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.