Systems and techniques for determining associations between multiple types of data in large data sets
US10552996B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 30, 2016 |
| Grant date | Feb 4, 2020 |
| Priority date | — |
| Expiry date | Dec 31, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/35
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods disclosed herein identify multivariate relationships that exist across all types data collected from numerous observed users over one or more networks. Electronic data collected from observed users include categorical data and non-categorical/numeric data. To compare and analyze the collected data, a marketing entity converts the numeric data to categorical data via a binning algorithm, which reduces the numeric data into two or more discrete categories. The marketing entity analyzes the data variables to compute pairwise associations on the collected categorical and numeric data (which has been converted to categorical data). The marketing entity also determines hierarchical clusters to group the pairwise associations of data variables based on the strength of the associations. The pairwise relationships and hierarchical clusters are displayed on a user interface.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.