Data compression using nearest neighbor cluster
US11977959B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 15, 2019 |
| Grant date | May 7, 2024 |
| Priority date | — |
| Expiry date | Feb 6, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/088
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Disclosed are techniques for compressing data in a data storage system comprising searching a cluster of nearest neighbors, wherein the cluster has been created using a locality sensitive hashing algorithm, to determine if a data block can be compressed. In alternate embodiments, nearest neighbor clusters can be formed using unsupervised learning. Additionally, nearest neighbors can also be formed in alternate embodiments using one or more of the following algorithms: a k-means clustering algorithm, a k-medoids clustering algorithm, a mean shift algorithm, a generalized method of moment (GMM) algorithm, or a density based spatial clustering of applications with noise (DBSCAN) algorithm.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.