Systems and methods for enabling natural language processing
View Patent ↗Systems and methods for searching databases by sound data input are provided herein. A service provider may have a need to make their database(s) searchable through search technology. However, the service provider may not have the resources to implement such search technology. The search technology may allow for search queries using sound data input. The technology described herein provides a solution addressing the service provider's need, by giving a search technology that furnishes search results in a fast, accurate manner. In further embodiments, systems and methods to monetize those search results are also described herein.
1. A method for processing natural language queries, the method comprising:
receiving two or more natural language libraries from service providers via a network, where each natural language library comprises:
natural language queries for interacting with a client application; and
responses for the natural language queries;
generating an aggregated natural language library from the received natural language libraries, wherein the aggregated natural language library includes a plurality of natural language sub-libraries, wherein at least two of the natural language sub-libraries are associated with different client applications that each provide a service;
receiving a search query via the network;
comparing the search query to the aggregated natural language library to determine at least one natural language query that corresponds to the search query; and
providing a response to the search query from the aggregated natural language library to a client device.
2. The method according to claim 1 , further comprising storing the two or more natural language libraries and the aggregated natural language library in a database.
3. The method according to claim 1 , wherein the plurality of natural language sub-libraries includes a plurality of aggregated natural language sub-libraries, each of the aggregated natural language sub-libraries comprising natural language libraries with substantially similar subject matter that are combined together.
4. The method according to claim 3 , further comprising providing access to an aggregated natural language sub-library to a service provider having a client application that provides a service that is substantially similar to the service associated with the aggregated natural language sub-library.
5. The method according to claim 1 , further comprising determining a natural language query for a requested service included in the search query, the search query comprising sound input.
6. The method according to claim 5 , wherein when the natural language query does not correspond to at least one query included in the aggregated natural language library, the natural language query is provided to a plurality of service providers that each have an application that provides a service that is substantially similar to the requested service associated with the natural language query.
7. The method according to claim 6 , further comprising receiving at least one response to the natural language query from the plurality of service providers.
8. The method according to claim 7 , further comprising receiving feedback from the client device regarding accuracy of the response.
9. The method according to claim 1 , wherein a natural language query comprises a request to interact with a client application that provides a service.
10. The method according to claim 1 , wherein the aggregated natural language library comprises a rule-based model for processing natural language queries.
11. A natural language query processor, comprising:
a memory for storing executable instructions;
a processor for executing instructions stored in memory to:
receive natural language libraries from service providers via a network, where each natural language library comprises:
natural language queries for interacting with a client application; and
responses for the natural language queries;
generate an aggregated natural language library from the received natural language libraries, wherein the aggregated natural language library includes a plurality of natural language sub-libraries, wherein at least two of the natural language sub-libraries are associated with different client applications that each provide a service;
receive a search query via the network from at least one client;
compare the search query to the aggregated natural language library to determine at least one natural language query that corresponds to the search query; and
provide a response to the search query from the aggregated natural language library to a client device.
12. The processor according to claim 11 , wherein the processor further stores the natural language libraries and the aggregated natural language library in a database.
13. The processor according to claim 11 , wherein the plurality of natural language sub-libraries includes a plurality of aggregated natural language sub-libraries, each of the aggregated natural language libraries comprising substantially similar natural language libraries that are combined together based upon a service associated with each of the substantially similar natural language libraries.
14. The processor according to claim 13 , wherein the processor further provides access to an aggregated natural language sub-library to a service provider having a different client application that provides a service that is substantially similar to the service associated with the aggregated natural language sub-library.
15. The processor according to claim 11 , wherein the processor further determines a natural language query included in the search query, the natural language query being associated with a requested service, the search query comprising sound input.
16. The processor according to claim 15 , wherein when the natural language query does not correspond to at least one natural language query included in the aggregated natural language library, the natural language query is provided to a plurality of service providers that each have an application that provides a service that is substantially similar to the requested service associated with the natural language query.
17. The processor according to claim 16 , wherein the processor further receives at least one response to the natural language query from the plurality of service providers.
18. The processor according to claim 17 , wherein the processor further receives feedback from the service provider regarding accuracy of the response.
19. The processor according to claim 11 , wherein a natural language query comprises a request to interact with a client application that provides a service.
20. A method for processing natural language queries, the method comprising:
receiving two or more natural language libraries from service providers via a network, the two or more natural language libraries comprising a customized natural language library, the customized natural language library comprising customized responses for natural language queries, wherein both the customized responses and the natural language queries are tailored to any of a service provider and a client application;
generating an aggregated natural language library from the received natural language libraries, wherein the aggregated natural language library includes a plurality of natural language sub-libraries, wherein at least two of the natural language sub-libraries are associated with different client applications that each provide a service;
receiving a search query via the network;
comparing the search query to the aggregated natural language library to determine a customized response that corresponds to the search query; and
providing the customized response that corresponds to the search query to a client device.
21. The method according to claim 20 , wherein the customized responses comprise any of an action relative to the client application, meta-data corresponding to an object, or combinations thereof.
22. The method according to claim 20 , further comprising selecting the customized natural language library based upon an accuracy of the customized response relative to other customized responses generated by other customized natural language libraries.
23. The method according to claim 20 , wherein the aggregated natural language library includes two or more customized natural language libraries.
24. The method according to claim 23 , further comprising periodically updating the aggregated natural language library by any of: adding one or more additional customized natural language libraries, updating at least one of the two or more customizable customized natural language libraries, or combinations thereof.
25. The method according to claim 20 , the customized natural language library comprising a rule-based model for processing natural language queries, the rule-based model being trained on natural language queries for interacting with a client application.