MANAGING INFERRED QUESTIONS

• US 20160078354A1
• Filed: 09/16/2014
• Published: 03/17/2016
• Est. Priority Date: 09/16/2014
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Pfeifer, Michael D., Rapp, William C., Petri, John E.
• Granted Patent: US 10,460,239 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation

Abstract

A system and computer implemented method for generating a set of inferred questions for a question answering system is disclosed. The method may include determining, based on context data, a user state. The method may also include extracting characterization information for an object satisfying an attention criteria. The characterization information may be configured to include sensory data. The method may also include determining a relationship between the object and the user state based on the characterization information for the object and the context data of the user state. The method may also include generating, based on the relationship between the object and the user state, a set of inferred questions for a question answering system.

Claims

1. A computer implemented method for generating a set of inferred questions for a question answering system, the method comprising:

determining, based on context data, a user state;

extracting characterization information for an object satisfying an attention criteria, wherein the characterization information is configured to include sensory data;

determining, using the characterization information for the object and a subset of the context data, a relationship between the object and the user state; and

generating, based on the relationship between the object and the user state, a set of inferred questions for a question answering system.

2. The method of claim 1, wherein the context data is configured to include a location, a physical condition, an interest score, and a focus area, and the sensory data is configured to include visual data, textual data, and audio data.

3. The method of claim 2, wherein determining the user state includes:

collecting, by a user monitoring system using a set of sensors, environment data and biometric data for the user; and

establishing, by analyzing the environment data and biometric data, the user state.

4. The method of claim 3, wherein the environment data includes at least one member of a group consisting of weather data, crowd density, noise level, and temperature, and the biometric data includes at least one member of a group consisting of heart rate data, eye movement data, gait data, posture data, and vocal data.

5. The method of claim 1, wherein the attention criteria is defined by at least a portion of user profile data for the user, and an attention threshold value calculated by an attention synthesis algorithm.

6. The method of claim 1, wherein determining the relationship between the object and the user state includes:

comparing the characterization information of the object with the subset of the context data; and

extracting a correlation between at least a portion of the characterization information and the subset of the context data.

7. The method of claim 1, wherein generating the set of inferred questions includes:

identifying, by a natural language processing technique configured to analyze metadata for both the sensory data and the context data, a query subject based on the characterization information of the physical object;

deriving, using an ontology database of structured affiliations, a set of subject modifiers for the query subject; and

formulating the set of inferred questions using the context data, the query subject, and the set of subject modifiers for the query subject.

8. The method of claim 3, further comprising:

determining, by the user monitoring system, that the user state includes a gaze having a gaze duration greater than a gaze threshold;

collecting, by a mobile device, characterization information including visual data, textual data, and audio data from a first object, wherein the first object is a target of the gaze;

comparing the characterization information of the first object with the subset of the context data;

extracting a correlation between the characterization information of the first object and the focus area of the user state; and

generating, based on the correlation between the characterization information of the first object and the focus area of the user state, a set of inferred questions for a question answering system.

9. The method of claim 8, wherein the mobile device is one or more selected from the group consisting of smart phones, tablets, smart watches, and wearable computing devices.

10. The method of claim 1, further comprising identifying the first object satisfying the attention criteria using a digital image processing algorithm configured to use one or more object recognition techniques including Scale-Invariant Feature Transform (SIFT).

11. A system for generating a set of inferred questions for a question answering system, the system comprising:

a collecting module configured to collect, using a set of sensors, context data including environment data and biometric data for a user;

an establishing module configured to establish, by analyzing the context data, a user state;

an extracting module configured to extract characterization information for an object satisfying an attention criteria, wherein the characterization information is configured to include sensory data;

a determining module configured to determine a relationship between the object and the user state based on the characterization information for the object and a subset of the context data; and

a generating module configured to generate, based on the relationship between the object and the user state, a set of inferred questions for a question answering system.

12. The system of claim 11, wherein the context data is configured to include a location, a physical condition, an interest score, and a focus area, and the sensory data is configured to include visual data, textual data, and audio data.

13. The system of claim 11, wherein the environment data includes weather data, crowd density, noise level, and temperature, and the biometric data includes heart rate, eye movement, gait, posture, and vocal data.

14. The system of claim 11, wherein the attention criteria is defined by at least a portion of user profile data for the user, and an attention threshold value calculated by an attention synthesis algorithm.

15. The system of claim 11, further comprising:

a comparing module configured to compare the characterization information of the physical object with the subset of the context data; and

an extracting module configured to extract a correlation between at least a portion of the characterization information and the subset of the context data.

16. The system of claim 11, further comprising:

an identifying module configured to identify, using a natural language processing technique configured to analyze metadata for both the sensory data and the context data, a query subject based on the characterization information of the physical object;

a deriving module configured to derive, using an ontology database of structured affiliations, a set of subject modifiers for the query subject; and

a formulating module configured to formulate the set of inferred questions using the context data, the query subject, and the set of subject modifiers for the query subject.

17. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a first computing device, causes the first computing device to:

collect, using a set of sensors, context data including environment data and biometric data for a user;

establish, by analyzing the context data, a user state;

extract characterization information for an object satisfying an attention criteria, wherein the characterization information is configured to include sensory data;

determine a relationship between the object and the user state based on the characterization information for the object and a subset of the context data;

identify, using a natural language processing technique configured to analyze metadata for both the sensory data and the context data, a query subject based on the characterization information of the physical object;

derive, using an ontology database of structured affiliations, a set of subject modifiers for the query subject; and

formulate a set of inferred questions using the context data, the query subject and the set of subject modifiers for the query subject.

18. The computer program product of claim 17, wherein the context data is configured to include a location, a physical condition, an interest score, and a focus area, and the sensory data is configured to include visual data, textual data, and audio data.

19. The computer program product of claim 17, wherein the environment data includes weather data, crowd density, noise level, and temperature, and the biometric data includes heart rate, eye movement, gait, posture, and vocal data.

20. The computer program product of claim 18, further comprising computer readable program code configured to:

determine, by the user monitoring system, that the user state includes a gaze having a gaze duration greater than a gaze threshold;

collect, by a mobile device, characterization information including visual data, textual data, and audio data from a first physical object, wherein the first physical object is a target of the gaze;

compare the characterization information of the first physical object with a subset of the context data;

extract a correlation between the characterization information of the first physical object and the focus area of the user state; and

generate, based on the correlation between the characterization information of the first physical objet and the focus of the user state, a set of inferred questions for a question answering system.