Automated document cluster merging for topic-based digital assistant interpretation
US10929613B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 27, 2018 |
| Grant date | Feb 23, 2021 |
| Priority date | — |
| Expiry date | Mar 7, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F40/131
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed are techniques for automatically extracting discovered topics and/or from determined discourse clusters for the generation of a language model that is applicable to interpreting commands received from a digital assistant device. An electronic document corpus can be generated having a plurality of documents that are clustered based on entropy, among other things. The clusters can be associated with a corresponding plurality of cluster attractors that are generally representative of a context of the documents included therein. The documents within the cluster for each of the document clusters can be analyzed, so that clusters determined representative of a hierarchical discourse community can be determined and logically merged. The merged clusters can be analyzed, such that topics and/or sub-topics can be determined and extracted therefrom, for indexing and storage, among other things. In this way, a more efficient searching of the electronic document corpus to interpret received inputs, such as commands received via a digital assistant device, can be facilitated.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.