Recommending data compression scheme using machine learning and statistical attributes of the data
US10715176B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 15, 2019 |
| Grant date | Jul 14, 2020 |
| Priority date | — |
| Expiry date | Apr 15, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH03M7/3079
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described herein is a system that facilitates recommending data compression using machine learning and statistical attributes. According to an embodiment, a system can comprise receiving a dataset, statistical attributes associated with the dataset, and a compression requirement for compression of the dataset. The system can further comprise based on the statistical attributes and the compression requirement, estimating a first compression attribute and a second compression attribute of a group of compression processes. The system can further comprise selecting a primary compression process from the group of compression processes, based on an output of an analytics component, wherein the analytics component employs a neural network to determine the primary compression process based on analysis of the statistical attributes, the compression requirement, and a compression objective.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.