Combining multiple clusterings by soft correspondence
US8195734B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 27, 2007 |
| Grant date | Jun 5, 2012 |
| Priority date | — |
| Expiry date | Apr 5, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/285
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because there is no explicit correspondence between the classes from different clusterings. Provided is a framework based on soft correspondence to directly address the correspondence problem in combining multiple clusterings. Under this framework, an algorithm iteratively computes the consensus clustering and correspondence matrices using multiplicative updating rules. This algorithm provides a final consensus clustering as well as correspondence matrices that gives intuitive interpretation of the relations between the consensus clustering and each clustering from clustering ensembles. Extensive experimental evaluations demonstrate the effectiveness and potential of this framework as well as the algorithm for discovering a consensus clustering from multiple clusterings.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.