TASK COMPLETION FOR NATURAL LANGUAGE INPUT

• US 20150278370A1
• Filed: 04/01/2014
• Published: 10/01/2015
• Est. Priority Date: 04/01/2014
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Kuo, Yu-Ting, McGovern, Andrew Paul, Wei, Xiao, Anand, Gaurav, Lusch, Adam C., Stratvert, Kevin Niels, Lin, Thomas
• Application Number:
  US14/242,394
• Publication Number:
  US 20150278370A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/90332 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30
• CPC Class Codes: H04L 67/60 Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources admission control or resource allocation H04L47/70

Abstract

One or more techniques and/or systems are provided for facilitating task completion. For example, a natural language input (e.g., “where should we eat”) may be received from a user of a client device. The natural language input may be evaluated using a set of user contextual signals, opted-in for exposure by the user for facilitating task completion, to identify a user task intent. For example, a user task intent of viewing a local Mexican restaurant menu may be identified based upon a social network post of the user indicating that the user is meeting a friend for Mexican food. Task completion functionality may be exposed to the user based upon the user task intent. For example, a restaurant app may be deep launched to display a menu of a local Mexican restaurant.

Claims

1. A method for facilitating task completion, comprising:

receiving a natural language input from a user of a client device;

evaluating the natural language input using a set of user contextual signals associated with the user to identify a user task intent; and

exposing task completion functionality to the user based upon the user task intent.

2. The method of claim 1, the exposing task completion functionality comprising:

identifying a task execution context based upon the user task intent, the task execution context comprising an application parameter; and

deep launching an application into a contextual state associated with the task execution context, the application populated with information corresponding to the application parameter.

3. The method of claim 1, the evaluating the natural language input comprising:

constructing a user intent query based upon the natural language input;

querying a task intent data structure using the user intent query to identify a global intent candidate; and

evaluating the global intent candidate using the set of user contextual signals to identify the user task intent.

4. The method of claim 3, the querying a task intent data structure comprising:

sending the user intent query to a server comprising the task intent data structure, the server remote to the client device; and

receiving the global intent candidate from the server.

5. The method of claim 3, the task intent data structure populated with one or more query to intent entries derived from community user search logs.

6. The method of claim 1, the exposing task completion functionality comprising:

executing an application configured to provide the task completion functionality.

7. The method of claim 1, the set of user contextual signals comprising at least one of a geolocation, a time, an executing application, an installed application, an app store application, calendar data, email data, social network data, a device form factor, a user search log, content consumed by the user, or community user intent for the natural language input.

8. The method of claim 1, the exposing task completion functionality comprising:

providing the user with access to at least one of a document, an application, an operating system setting, a music entity, a video, a photo, a social network profile, a map, or a search result.

9. The method of claim 4, comprising:

identifying user feedback for the task completion functionality; and

providing the user feedback to the server for training a task intent model used to populate the task intent data structure.

10. The method of claim 1, the natural language input comprising a voice command provided by the user.

11. The method of claim 1, the exposing task completion functionality comprising:

deep launching an application based upon the user task intent, the deep launching comprising;

identifying a current location of the user;

identifying a set of entity candidates corresponding to the user task intent;

selecting an entity candidate from the set of entity candidates based upon a proximity of the entity candidate to the current location; and

populating the application within information associated with the entity candidate.

12. The method of claim 1, comprising:

providing a user refinement interface to the user based upon the user task intent;

receiving a user task refinement input through the user refinement interface; and

revising the user task intent based upon the user task refinement input.

13. A system for facilitating task completion comprising:

a task intent training component configured to;

evaluate community user search log data to train a task intent model; and

utilize the task intent model to populate a task intent data structure with one or more query to intent entries; and

a user intent provider component configured to;

receive a user intent query from a client device, the user intent query derived from a natural language input received on the client device;

query the task intent data structure using the user intent query to identify a global intent candidate; and

provide the global intent candidate to the client device for facilitating task completion associated with a user task intent derived from the natural language input.

14. The system of claim 13, the task intent training component configured to:

receive user feedback for the global intent candidate; and

train the task intent model based upon the user feedback.

15. A system for facilitating task completion, comprising:

a task facilitator component configured to;

receive a natural language input from a user of a client device;

evaluate the natural language input using a set of user contextual signals associated with the user to identify a user task intent;

identify a task execution context based upon the user task intent; and

deep launch an application into a contextual state associated with the task execution context.

16. The system of claim 15, the task facilitator component configured to:

specify an application parameter for the task execution context; and

populate the application with information corresponding to the application parameter.

17. The system of claim 15, the task facilitator component configured to:

construct a user intent query based upon the natural language input;

query a task intent data structure using the user intent query to identify a global intent candidate; and

evaluate the global intent candidate using the set of user contextual signals to identify the user task intent.

18. The system of claim 17, the task facilitator component configured to:

send the user intent query to a server comprising the task intent data structure, the server remote to the client device; and

receive the global intent candidate from the server.

19. The system of claim 15, the set of user contextual signals comprising at least one of a geolocation, a time, an executing application, an installed application, and app store application, calendar data, email data, social network data, a device form factor, a user search log, content consumed by the user, or community user intent for the natural language input.

20. The system of claim 15, the task facilitator component configured to:

provide a user refinement interface to the user based upon the user task intent;

receive a user task refinement input through the user refinement interface; and

revise the user task intent based upon the user task refinement input.