Knowledge discovery from citation networks
US9892367B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 22, 2016 |
| Grant date | Feb 13, 2018 |
| Priority date | — |
| Expiry date | Apr 15, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q10/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In a corpus of scientific articles such as a digital library, documents are connected by citations and one document plays two different roles in the corpus: document itself and a citation of other documents. A Bernoulli Process Topic (BPT) model is provided which models the corpus at two levels: document level and citation level. In the BPT model, each document has two different representations in the latent topic space associated with its roles. Moreover, the multi-level hierarchical structure of the citation network is captured by a generative process involving a Bernoulli process. The distribution parameters of the BPT model are estimated by a variational approximation approach.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.