Automatic identification of misclassified elements of an infrastructure model
US11645363B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 20, 2020 |
| Grant date | May 9, 2023 |
| Priority date | — |
| Expiry date | Nov 7, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2200/24
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In example embodiments, techniques are provided to automatically identify misclassified elements of an infrastructure model using machine learning. In a first set of embodiments, supervised machine learning is used to train one or more classification models that use different types of data describing elements (e.g., a geometric classification model that uses geometry data, a natural language processing (NLP) classification model that uses textual data, and an omniscient (Omni) classification model that uses a combination of geometry and textual data; or a single classification model that uses geometry data, textual data, and a combination of geometry and textual data). Predictions from classification models (e.g., predictions from the geometric classification model, NLP classification model and the Omni classification model) are compared to identify misclassified elements, or a prediction of misclassified elements directly produced (e.g., from the single classification model). In a second set of embodiments, unsupervised machine learning is used to detect abnormal associations in data describing elements (e.g., geometric data and textual data) that indicate misclassifications. Iden…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.