Machine learning repository service
US-2019278640-A1 · Sep 12, 2019 · US
US2021192375A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2021192375-A1 |
| Application number | US-202117249584-A |
| Country | US |
| Kind code | A1 |
| Filing date | Mar 5, 2021 |
| Priority date | Sep 20, 2018 |
| Publication date | Jun 24, 2021 |
| Grant date | — |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
An artificial intelligence device for identifying an object in a data set includes processing circuitry configured to receive the data set and a query including object. The processing circuitry selects one or more models using an entity knowledge database that includes a plurality of entities corresponding to objects to be identified. Each of a plurality or recognition models is linked to multiple entities of the entity knowledge database so that the processing circuitry may select multiple recognition models. The processing circuitry then processes the data set using the selected recognition model or models to provide an indication of whether the data set includes the at least one object. The entities may be ontologically coupled in the database so that, even if the object does not have a corresponding entity in the database, the object may be identified using models selected based on the ontology.
Opening claim text (preview).
What is claimed is: 1 . A device for identifying at least one object in a data set, the device comprising: a memory comprising instructions; and one or more processors in communication with the memory, wherein the one or more processors execute the instructions to: receive a data set and a query to including the at least one object in the data set; select at least one recognition model using an entity knowledge database including a plurality of entities corresponding to objects to be identified, wherein each recognition model of a plurality or recognition models is linked to multiple entities of the entity knowledge database; and process the data set using the at least one selected recognition model to provide an indication of whether the data set includes the at least one object. 2 . The device of claim 1 , wherein the one or more processors execute further instructions to: receive the plurality of recognition models, each recognition model including at least one annotation; and for each recognition model: identify at least one entity of the entity knowledge database that corresponds to the recognition model, based on the at least one annotation of the recognition model; and link the recognition model to the at least one entity in the entity knowledge database. 3 . The device of claim 1 , wherein: the at least one recognition model includes multiple recognition models and each recognition model of the multiple recognition models includes at least one parameter indicating computing resources to be used to process the data set using the recognition model; and the one or more processors execute the instructions to process the data set by processing the data set using at least one recognition model from the multiple recognition models, the at least one recognition model having indicated computing resources that are compatible with resources available to the one or more processors. 4 . The device of claim 1 , wherein the one or more processors execute the instructions to obtain additional resources from a network-connected service before selecting the recognition model. 5 . The device of claim 1 , wherein: the entity knowledge database is a graph database; the entities of the entity knowledge graph database are ontologically coupled nodes of the entity knowledge graph database such that a recognition model which is directly linked to one node in the entity knowledge database is linked to all nodes in the entity knowledge database that are ontologically coupled to the one node; the entity knowledge graph database includes a node corresponding to the at least one object and the node corresponding to the at least one object is not directly linked to a recognition model; and the one or more processors execute the instructions to select, as the at least one recognition model, one or more recognition models directly linked to at least one node in the entity knowledge database that is ontologically coupled to the node corresponding to the at least one object. 6 . The device of claim 1 , wherein the one or more processors execute the instructions to: select, as the one or more recognition models associated with the ontologically coupled nodes, a plurality of recognition models linked to a respective plurality of nodes ontologically coupled to the node corresponding to the at least one object; process the data set using the selected plurality of recognition models; and combine results of processing the selected plurality of recognition models to provide the indication of whether the data set includes the at least one object. 7 . The device of claim 1 , wherein: the entity knowledge database is a graph database; and the entity knowledge graph database includes a plurality of ontologically organized nodes corresponding to the at least one object at different levels of generality and the one or more processors execute the instructions to: select, as the at least one recognition model, a plurality of recognition models associated with the plurality of nodes corresponding to the different levels of generality of the at least one object; process the data set using the selected plurality of recognition models; and combine results of the processing of the selected plurality of recognition models to provide the indication of whether the data set includes the at least one object. 8 . A method for identifying an object in a data set, the method comprising: searching an entity knowledge database including a plurality of nodes corresponding to objects to be identified, wherein each recognition model of a plurality of recognition models is linked to multiple nodes of the entity knowledge database; selecting at least one recognition model of the plurality of recognition models to be used to identify the at least one object in response to the search of the entity knowledge database; and processing the data set using the at least one selected recognition model to provide an indication of whether the data set includes the at least one object. 9 . The method of claim 8 , further comprising: receiving the plurality of recognition models, each recognition model including at least one annotation; and for each recognition model: identifying at least one entity of the entity knowledge database that corresponds to the recognition model, based on the at least one annotation of the recognition model; and linking the recognition model to the at least one entity in the entity knowledge database. 10 . The method of claim 8 , wherein: the at least one recognition model includes multiple recognition models and each recognition model of the multiple recognition models includes at least one parameter indicating computing resources to be used to process the data set using the recognition model; and the method further comprises processing the data set using at least one recognition model from the multiple recognition models, the at least one recognition model having indicated computing resources that are compatible with resources available to the one or more processors. 11 . The method of claim 8 , further comprising obtaining additional resources from a network-connected service before selecting the recognition model. 12 . The method of claim 8 , wherein: the entity knowledge database is a graph database having entities that are ontologically coupled to nodes of the entity knowledge graph database such that a recognition model which is directly linked to one node in the entity knowledge database is linked to all nodes in the entity knowledge database that are ontologically coupled to the one node and the entity knowledge graph database includes a node corresponding to the at least one object and the node corresponding to the at least one object is not directly linked to a recognition model; and the method further comprises selecting, as the at least one recognition model, one or more recognition models directly linked to at least one node in the entity knowledge database that is ontologically coupled to the node corresponding to the at least one object. 13 . The method of claim 8 , further comprising: selecting, as the one or more recognition models associated with the ontologically coupled nodes, a plurality of recognition models linked to a respective plurality of nodes ontologically coupled to the node corresponding to the at least one object; processing the data set using the selected plurality of recognition models; and combining results of processing the selected plurality of recognition models to provide the indication of whether the data set includes the at least one object. 14 . The method of
using metadata automatically derived from the content · CPC title
Inference or reasoning models · CPC title
Selection of pattern recognition techniques, e.g. of classifiers in a multi-classifier system · CPC title
Querying · CPC title
structured as a network, e.g. client-server architectures · CPC title
Related publications grouped by family.
Answers are generated from the same data shown on this page.