Personalized entity repository
Systems and methods are provided for a personalized entity repository. For example, a computing device comprises a personalized entity repository having fixed sets of entities from an entity repository stored at a server, a processor, and memory storing instructions that cause the computing device to identify fixed sets of entities that are relevant to a user based on context associated with the computing device, rank the fixed sets by relevancy, and update the personalized entity repository using selected sets determined based on the rank and on set usage parameters applicable to the user. In another example, a method includes generating fixed sets of entities from an entity repository, including location-based sets and topic-based sets, and providing a subset of the fixed sets to a client, the client requesting the subset based on the client's location and on items identified in content generated for display on the client.
1. A method implemented by one or more processors, the method comprising:
receiving a screen capture image, the screen capture image capturing content displayed on a display of a mobile device;
determining text in the screen capture image by performing text recognition on the screen capture image;
processing the text using a trained set prediction model to predict one or more fixed sets of entities based on the text;
storing at least one fixed set of entities of the predicted fixed sets of entities in a personalized entity repository in memory on the mobile device; and
subsequent to storing the at least one fixed set of entities:
using the stored at least one fixed set of entities to identify an entity in an additional screen capture image captured at the mobile device; and
rendering, at the mobile device, content that is based on the identified entity.
2. The method of claim 1 , further comprising:
determining a location associated with content recognized in a further screen capture image;
processing the location using the trained set prediction model to predict at least one location-based fixed set of entities based on the location; and
storing the at least one location-based fixed set of entities in the personalized entity repository.
3. The method of claim 2 , further comprising:
using the stored at least one location-based fixed set of entities to identify a location-based entity based on data captured at the mobile device; and
rendering, at the mobile device, further content that is based on the identified location-based entity.
4. The method of claim 1 , wherein the trained set prediction model predicts a plurality of predicted fixed sets of entities and the method further comprises:
ranking each of the predicted fixed sets of entities;
using set usage parameters and the rankings to determine selected fixed sets of entities from the predicted fixed sets of entities, the selected fixed set of entities including the at least one fixed set of entities; and
storing the selected fixed sets of entities in the personalized entity repository.
5. The method of claim 4 , wherein the set usage parameters includes a quantity of fixed sets.
6. The method of claim 4 , wherein the set usage parameters include an amount of memory allocated to the personalized entity repository.
7. A mobile device comprising:
a display device;
a personalized entity repository stored in memory, the personalized entity repository including a plurality of fixed sets of entities from an entity repository stored at a server, wherein each fixed set has a respective identifier and includes information about the entities in the set;
at least one processor; and
memory storing instructions that, when executed by the at least one processor, cause the mobile device to:
capture a screen capture image that captures content displayed on the display device;
cause text in the screen capture image to be processed using a trained set prediction model to predict one or more fixed sets of entities based on the text;
store at least one fixed set of entities of the predicted fixed sets of entities in the personalized entity repository stored in the memory on the mobile device; and
subsequent to storing the at least one fixed set of entities:
use the stored at least one fixed set of entities to identify an entity in an additional screen capture image captured at the mobile device; and
render, via the display device, content that is based on the identified entity.
8. The mobile device of claim 7 , the memory further storing instructions that, when executed by the at least one processor, cause the mobile device to:
cause a location, determined via data captured at the mobile device, to be processed using the trained set prediction model to predict at least one location-based fixed set of entities based on the location; and
store the at least one location-based fixed set of entities in the personalized entity repository stored in the memory on the mobile device.
9. The mobile device of claim 8 , the memory further storing instructions that, when executed by the at least one processor, cause the mobile device to:
use the stored at least one location-based fixed set of entities to identify a location-based entity based on further data captured at the mobile device; and
render, via the display device, further content that is based on the identified location-based entity.
10. The mobile device of claim 7 , wherein the trained set prediction model predicts a plurality of predicted fixed sets of entities, ranks each of the predicted fixed sets of entities, and uses the set usage parameters and the rankings to determine selected fixed sets of entities from the predicted fixed sets of entities, wherein the selected fixed set of entities include the at least one fixed set of entities.
11. The mobile device of claim 10 , wherein the set usage parameters includes a quantity of fixed sets.
12. The mobile device of claim 10 , wherein the set usage parameters include an amount of memory allocated to the personalized entity repository.
13. A method implemented by one or more processors, the method comprising:
receiving a screen capture image, the screen capture image capturing content displayed on a display of a mobile device,
processing the screen capture image to determine a location associated with the content displayed in the screen capture image;
processing the location using a trained set prediction model to predict one or more fixed sets of entities based on the location;
storing at least one fixed set of entities of the predicted fixed sets of entities in a personalized entity repository in memory on the mobile device; and
subsequent to storing the at least one fixed set of entities:
using the stored at least one fixed set of entities to identify an entity in an additional screen capture image captured at the mobile device; and
rendering, at the mobile device, content that is based on the identified entity.
14. The method of claim 13 , wherein the trained set prediction model predicts a plurality of predicted fixed sets of entities and the method further comprises:
ranking each of the predicted fixed sets of entities;
using set usage parameters and the rankings to determine selected fixed sets of entities from the predicted fixed sets of entities, the selected fixed set of entities including the at least one fixed set of entities; and
storing the selected fixed sets of entities in the personalized entity repository.
15. The method of claim 14 , wherein the set usage parameters includes a quantity of fixed sets.
16. The method of claim 15 , wherein the set usage parameters include an amount of memory allocated to the personalized entity repository.
17. The method of claim 14 , wherein the set usage parameters include an amount of memory allocated to the personalized entity repository.