Method and system for improving content searching in a question and answer customer support system by using a crowd-machine learning hybrid predictive model
US10467541B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 27, 2016 |
| Grant date | Nov 5, 2019 |
| Priority date | — |
| Expiry date | Feb 24, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and system improves content searching in a question and answer customer support system by using a crowd-machine learning hybrid predictive model, according to one embodiment. The question and answer customer support system determines which customer support content to provide to users by using the hybrid predictive model, according to one embodiment. The question and answer customer support system receives a search query from a user and applies the search query (or a representation of the search query) to the hybrid predictive model, according to one embodiment. The hybrid predictive model generates a likelihood that particular customer support content is relevant to a user's search query, according to one embodiment. The question and answer customer support system acquires user feedback from users and updates/trains the hybrid predictive model based on the user feedback, according to one embodiment.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.