Topic model based clustering of text data with machine learning utilizing interface feedback
US10803399B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 10, 2015 |
| Grant date | Oct 13, 2020 |
| Priority date | — |
| Expiry date | Nov 4, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/93
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An apparatus comprises a processing platform configured to implement a machine learning system for automated classification of documents comprising text data of at least one database. The machine learning system comprises a clustering module configured to assign each of the documents to one or more of a plurality of clusters corresponding to respective topics identified from the text data in accordance with at least one topic model, and an interface configured to present portions of documents assigned to a particular one of the clusters by the clustering module and to receive feedback regarding applicability of the corresponding topic to each of one or more of the presented portions on a per-portion basis. The topic model is updated based at least in part on the received feedback. The feedback may comprise, for example, selection of a confidence level for applicability of the topic to a given one of the presented portions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.