Conversational relevance modeling using convolutional neural network
US11593613B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 4, 2017 |
| Grant date | Feb 28, 2023 |
| Priority date | — |
| Expiry date | Jan 1, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Non-limiting examples of the present disclosure describe a convolutional neural network (CNN) architecture configured to evaluate conversational relevance of query-response pairs. A CNN model is provided that can include a first branch, a second branch, and multilayer perceptron (MLP) layers. The first branch includes convolutional layers with dynamic pooling to process a query. The second branch includes convolutional layers with dynamic pooling to process candidate responses for the query. The query and the candidate responses are processed in parallel using the CNN model. The MLP layers are configured to rank query-response pairs based on conversational relevance.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.