Using cohorts to infer attributes for an input case in a question answering system

Patent metadata

Field	Value
Publication number	US-9747552-B2
Application number	US-201514658973-A
Country	US
Kind code	B2
Filing date	Mar 16, 2015
Priority date	Feb 19, 2015
Publication date	Aug 29, 2017
Grant date	Aug 29, 2017

Abstract

A cohort analysis mechanism analyzes cohorts to infer one or more additional attributes for an input case to provide a refined input case to answer a question in a question answering system. The refined input case is then used to answer a question in the question answering system. The refined input case can be used in a traditional question answering flow or in a flow that again uses cohort analysis to extract relevant data to answer the question. The cohort analysis mechanism analyzes cohorts to find common attributes in the cohorts and then determines whether to infer the common attributes into the refined input case. The cohort analysis mechanism may determine to dialog with a user to confirm an inferred attribute.

First claim

The invention claimed is:

1. An apparatus comprising:
at least one processor;
a memory coupled to the at least one processor;
a cohort analysis mechanism residing in the memory and executed by the at least one processor that analyzes an input case representing a question to determine whether cohorts can be used with the input case, wherein the cohorts are similar entities with similar characteristics to an entity of the input case and available in a corpus of data;
wherein the cohort analysis mechanism uses cohort analysis to infer an attribute for the input case by:
determining if the input case has an entity that has available cohorts;
identifying cohorts in the corpus of data using fuzzy matching with a threshold percentage and where the cohorts are similar to the entity in the input case;
analyzing the cohorts to find common attributes in the cohorts;
finding missing attributes for the entity of the input case from the common attributes in the cohorts to infer a missing attribute for the input case;
scoring the missing attributes according to consistency and sample size;
applying confidence thresholds to the missing attributes to determine whether to infer the attribute for the refined input case;
determining whether to dialog with a user to confirm the inferred attribute using a lower threshold compared to inferring the attribute without dialoging with the user;

generating a refined input case that includes the inferred attribute applied to the entity of the input case; and
using the refined input case with the inferred attribute to answer the question.

2. The apparatus of claim 1 wherein the input case is a medical question for a patient and the cohort analysis mechanism processes the medical history of the patient and cohorts, wherein the cohorts comprise a set of other patients with similar attributes, by processing medical histories of other patients to infer the attribute for the refined input case from the cohorts.

3. The apparatus of claim 1 wherein the cohort analysis mechanism is part of a question answering application that answers a natural language question.

4. An apparatus comprising:
at least one processor;
a memory coupled to the at least one processor;
a cohort analysis mechanism residing in the memory and executed by the at least one processor that analyzes an input case representing a question, wherein the input case is a medical question about a patient, and wherein cohorts comprise a set of other patients with similar attributes;
wherein the cohort analysis mechanism uses cohort analysis to infer an attribute for the input case by:
identifying similar patients in the corpus of data where the similar patients are similar to the patient in the input case;
analyzing the similar patients to find common attributes in the similar patients;
scoring the missing attributes according to consistency and sample size;

finding missing attributes for the patient of the input case from the common attributes in the similar patients to infer an attribute for the input case from the missing attributes;
generating a refined input case that includes the inferred attribute from the common attributes of the similar patients; and
using the refined input case with the inferred attribute to answer the question by submitting the refined input case with the inferred attribute to the question answering system.

5. A program product comprising:
a cohort analysis mechanism that analyzes an input case representing a question to determine whether cohorts can be used with the input case, wherein the cohorts are similar entities with similar characteristics to an entity of the input case and available in a corpus of data;
wherein the cohort analysis mechanism uses cohort analysis to infer an attribute for the input case by:
determining if the input case has an entity that has available cohorts;
identifying cohorts in the corpus of data using fuzzy matching with a threshold percentage and where the cohorts are similar to the entity in the input case;
analyzing the cohorts to find common attributes in the cohorts;
finding missing attributes for the entity of the input case from the common attributes in the cohorts to infer a missing attribute for the input case;
scoring the missing attributes according to consistency and sample size;
applying confidence thresholds to the missing attributes to determine whether to infer the attribute for the refined input case;
determining whether to dialog with a user to confirm the inferred attribute using a lower threshold compared to inferring the attribute without dialoging with the user;

generating a refined input case that includes the inferred attribute applied to the entity of the input case; and
using the refined input case with the inferred attribute to answer the question; and
a non-transistory computer-readable storage medium bearing the cohort analysis mechanism.

6. The program product of claim 5 wherein the input case is a medical question for a patient and the cohort analysis mechanism processes the medical history of the patient and cohorts, wherein the cohorts comprise a set of other patients with similar attributes, by processing medical histories of other patients to infer the attribute for the refined input case from the cohorts.

7. The program product of claim 5 wherein the cohort analysis mechanism is part of a question answering application that answers a natural language question.

8. The program product of claim 5 wherein the cohorts are people.

9. The program product of claim 5 wherein the cohorts are chosen from one of the following: patients, animals, and computer components.

Assignees

• IBM

Inventors

• Clark Adam T
• Huebert Jeffrey K
• Payton Aspen L
• Petri John E
• Stevens Richard J
• Whaley Kathryn L

Classifications

• G06N5/04 Primary

  Inference or reasoning models · CPC title

• G06F17/3043

  Physics · mapped topic

• G06F16/90332

  Natural language query formulation or dialogue systems · CPC title

• G06F16/90324

  using system suggestions · CPC title

• G06F16/24522

  Translation of natural language queries to structured queries · CPC title