Dynamic word correlated topic machine learning model
US12050872B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 15, 2021 |
| Grant date | Jul 30, 2024 |
| Priority date | — |
| Expiry date | Jun 28, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F40/216
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system implements a dynamic word correlated topic model (DWCTM) to model an evolution of topic popularity, word embedding, and topic correlation within a set of documents, or other dataset, that spans a period of time. For example, the DWCTM receives the set of documents and a quantity of topics for modeling. The DWCTM processes the set computing, for each topic, various distributions to capture a popularity, word embedding, and correlation with other topics across the period of time. In other examples, a dataset of user listening sessions comprised of media content items for modeling by the DWCTM. Media content metadata (e.g., artist or genre) of the media content items, similar to words of a document, can be modeled by the DWCTM.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.