Ranking relevant attributes of entity in structured knowledge base
US9229988B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 18, 2013 |
| Grant date | Jan 5, 2016 |
| Priority date | — |
| Expiry date | Jun 1, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/90
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Architecture that addresses at least the problem of ranking the relevant attributes for a given entity within the context of a structured knowledge base (SKB). The architecture utilizes the attribute, entity type statistics, and the taxonomy of the attributes to consistently and efficiently rank attributes for each and every type of entity in the SKB. Using the SKB, intermediate features are computed, including the importance or popularity each entity type for every entity, inverse document frequency (IDF) computation for each attribute on a global basis, IDF computation for entity types, and the popularity of attributes for each entity type. The intermediate features are aggregated to obtain a final feature set, which can be used in combination with human judgments to train a machine learned classifier model to produce and predict a relevance score for a given entity and each of its attributes. The attributes are ranked for each entity using this score.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.