IP Library Granted Patent US 9,158,772
Granted Patent B2
US 9,158,772 · App. 13/717,105 · Granted Oct 13, 2015

Partial and parallel pipeline processing in a deep question answering system

Inventors: Adam T. Clark (Mantorville, MN); Mark G. Megerian (Rochester, MN); John E. Petri (St. Charles, MN); Richard J. Stevens (Monkton, VT)
Assignee: International Business Machines Corporation
G06F17/30038G06F17/30675
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Quick Facts
Patent No.
US 9,158,772
App. No.
13/717,105
Granted
Oct 13, 2015
Kind
B2
Abstract

System, method, and computer program product to reduce an amount of processing required to generate a response to a first case by a deep question answering system, by, determining that a similarity score, of the first case relative to a second case, exceeds a similarity threshold, identifying a first feature of the second case having a first relevance score exceeding a relevance threshold, identifying a first candidate answer for the first case that does not have the first feature, and refraining from analyzing the first candidate answer in generating the response to the first case, thereby reducing the amount of processing of the deep question answering system.

Claims (44)

1. A computer program product to reduce an amount of processing required to generate a response to a first case by a question answering system, the computer program product comprising:

a non-transitory computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code comprising:

computer-readable program code configured to determine that a similarity score, of the first case relative to a second case, exceeds a similarity threshold;

computer-readable program code configured to identify a first feature of the second case having a first relevance score exceeding a relevance threshold, wherein the relevance score indicates that the first feature is relevant in generating a correct response to the second case;

computer-readable program code configured to determine, based on the similarity score and the first relevance score, that the first feature is relevant in generating a correct response to the first case;

computer-readable program code configured to identify a first candidate answer for the first case that does not have the first feature; and

computer-readable program code configured to refrain from analyzing the first candidate answer in generating the response to the first case, thereby reducing the amount of processing of the question answering system.

2. The computer program product of claim 1 , further comprising:

computer-readable program code configured to analyze a second candidate answer in generating a response to the first case upon determining that the second candidate answer has the first feature.

3. The computer program product of claim 1 , wherein refraining from analyzing the first candidate answer comprises:

refraining from performing natural language processing on the first candidate answer;

refraining from determining whether the first candidate answer has a second feature, wherein the question answering system has identified the second feature has a second relevance score exceeding the relevance threshold;

refraining from retrieving supporting evidence for the first candidate answer; and

refraining from scoring the supporting evidence for the first candidate answer.

4. The computer program product of claim 1 , wherein the similarity score is computed based on a context of the first case matching a context of the second case.

5. The computer program product of claim 1 , further comprising:

computer-readable program code configured to, upon determining that: (i) a utilization of a resource of the question answering system does not exceed a utilization threshold, and (ii) a confidence score of a first response generated by refraining to analyze the first candidate answer exceeds a confidence threshold, generate a second response to the case, wherein the first candidate answer is analyzed in generating the second response to the case.

6. The computer program product of claim 1 , wherein identifying the first feature of the second case as having the first relevance score exceeding the relevance threshold is based on a stored dependency of the second case to the first feature.

7. The computer program product of claim 1 , wherein the first case comprises at least one question presented to the question answering system.

8. The computer program product of claim 7 , wherein the first feature comprises at least one of: (i) a type, (ii) a subject matter, (iii) a variable, and (iv) a context of the at least one question.

9. A system, comprising:

one or more computer processors; and

a memory containing a program, which, when executed by the one or more computer processors, performs an operation to reduce an amount of processing required to generate a response to a first case by a question answering system, the operation comprising:

determining that a similarity score, of the first case relative to a second case, exceeds a similarity threshold;

identifying a first feature of the second case having a first relevance score exceeding a relevance threshold, wherein the relevance score indicates that the first feature is relevant in generating a correct response to the second case;

determining, based on the similarity score and the first relevance score, that the first feature is relevant in generating a correct response to the first case;

identifying a first candidate answer for the first case that does not have the first feature; and

refraining from analyzing the first candidate answer in generating the response to the first case, thereby reducing the amount of processing of the question answering system.

10. The system of claim 9 , the operation further comprising:

responsive to receiving a second case by the question answering system:

classifying the second case;

computing the similarity score; and

upon determining that the similarity score exceeds a specified similarity threshold, identifying the first feature as relevant in generating a correct response to the second case.

11. The system of claim 9 , the operation further comprising:

analyzing a second candidate answer in generating a response to the first case upon determining that the second candidate answer has the first feature.

12. The system of claim 9 , wherein refraining from analyzing the first candidate answer comprises:

refraining from performing natural language processing on the first candidate answer;

refraining from determining whether the first candidate answer has a second feature, wherein the question answering system has identified the second feature has a second relevance score exceeding the relevance threshold;

refraining from retrieving supporting evidence for the first candidate answer; and

refraining from scoring the supporting evidence for the first candidate answer.

13. The system of claim 9 , wherein the similarity score is computed based on a context of the first case matching a context of the second case.

14. The system of claim 9 , wherein identifying the first feature of the second case as having the first relevance score exceeding the relevance threshold is based on a stored dependency of the second case to the first feature.

15. The system of claim 9 , wherein the first case comprises at least one question presented to the question answering system.

16. The system of claim 15 , wherein the first feature comprises at least one of: (i) a type, (ii) a subject matter, (iii) a variable, and (iv) a context of the at least one question.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 17, 2017
From: INTERNATIONAL BUSINESS MACHINES CORPORATION
To: SINOEAST CONCEPT LIMITED
Reel/Frame 041388/0557 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 17, 2012
From: CLARK, ADAM T.; MEGERIAN, MARK G.; PETRI, JOHN E.; STEVENS, RICHARD J.
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 029483/0922 →
Continuity (1)
Related Publication 20140172882A1 · Jun 19, 2014