Methods and apparatus for feature generation using improved term frequency-inverse document frequency (TF-IDF) with deep learning for accurate cloud asset tagging
US11748621B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 8, 2022 |
| Grant date | Sep 5, 2023 |
| Priority date | — |
| Expiry date | Nov 8, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An embodiment includes generating an input document that includes a plurality of text fields of attribute data. The embodiment also includes extracting a set of candidate features from the attribute data using a feature extraction module that evaluates the attribute data using first and second machine learning models, where the first machine learning model scores terms in the input document and the second machine learning model includes a deep learning model. The embodiment also includes calculating feature-selection values for respective features of the set of candidate features and generating tag information for a remote computing asset using a machine learning classifier that predicts the tag information based on the feature-selection values.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.