Service labeling using semi-supervised learning
US11659026B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 22, 2020 |
| Grant date | May 23, 2023 |
| Priority date | — |
| Expiry date | Nov 7, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L67/1008
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
The disclosure provides an approach for workload labeling and identification of known or custom applications. Embodiments include determining a plurality of sets of features comprising a respective set of features for each respective workload of a first subset of a plurality of workloads. Embodiments include identifying a group of workloads based on similarities among the plurality of sets of features. Embodiments include receiving label data from a user comprising a label for the group of workloads. Embodiments include associating the label with each workload of the group of workloads to produce a training data set. Embodiments include using the training data set to train a model to output labels for input workloads. Embodiments include determining a label for a given workload of the plurality of workloads by inputting features of the given workload to the model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.