Answer sequence evaluation

Patent metadata

Field	Value
Publication number	US-2016125298-A1
Application number	US-201414570797-A
Country	US
Kind code	A1
Filing date	Dec 15, 2014
Priority date	Nov 5, 2014
Publication date	May 5, 2016
Grant date	—

Abstract

Aspects of the present disclosure are directed toward evaluating an answer sequence. Aspects are directed toward receiving a set of answer sequences including a first answer sequence. The first answer sequence may have a first set of answers. Aspects are also directed toward identifying a set of scores coupled with the first set of answers. Aspects are also directed toward determining, based on a subject matter corresponding to the first answer sequence, a set of evaluation rules. Aspects are also directed toward generating, based on the set of scores and the set of evaluation rules, a sequence evaluation score for the first answer sequence.

First claim

1 - 12 . (canceled)

13 . A computer system, comprising:
at least one processor; a memory coupled to the at least one processor; an answer sequence evaluation mechanism executed by one or more of the at least one processor, the answer sequence evaluation mechanism including: a receiving module to receive a set of answer sequences including a first answer sequence having a first set of answers; an identifying module to identify a set of scores coupled with the first set of answers; a first determining module to determine, based on a subject matter corresponding to the first answer sequence, a set of evaluation rules; and a generating module to generate, based on the set of scores and the set of evaluation rules, a sequence evaluation score for the first answer sequence.

14 . The system of claim 13 , further comprising:
a computing module to compute, based on the subject matter, a caution value for the first answer sequence; a second determining module to determine, by comparing the caution value to a first caution threshold, that the caution value achieves the first caution threshold; and a selecting module to select, in response to determining that the caution value achieves the first caution threshold, a first evaluation rule.

15 . The system of claim 14 , wherein:
the first evaluation rule identifies, from the set of scores coupled with the first set of answers, a first score of the set of scores, wherein the first score does not achieve a first score threshold; and generating the sequence evaluation score for the first answer sequence includes assigning, to the first answer sequence, the first score as the sequence evaluation score.

16 . The system of claim 14 , further comprising:
a third determining module to determine, by comparing the caution value to a second caution threshold, that the caution value does not achieve the second caution threshold; a second selecting module to select, in response to determining that the caution value does not achieve the second caution threshold, a second evaluation rule.

17 . The system of claim 16 , wherein:
the second evaluation rule calculates, by performing a statistical algorithm on the set of scores, an aggregate score; and generating the sequence evaluation score for the first answer sequence comprises assigning, to the first answer sequence, the aggregate score as the sequence evaluation score.

18 . 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 computing device to:
receive a set of answer sequences including a first answer sequence having a first set of answers; identify a set of scores coupled with the first set of answers; determine, based on a subject matter corresponding to the first answer sequence, a set of evaluation rules; and generate, based on the set of scores and the set of evaluation rules, a sequence evaluation score for the first answer sequence.

19 . The computer program product of claim 18 , further comprising computer readable program code configured to:
evaluate, using a natural language processing technique configured to parse semantic and syntactic content, context data; determine, in response to evaluating the context data, that the context data achieves a satisfaction criterion; and select, in response to determining that the context data achieves the satisfaction criterion, a third evaluation rule.

20 . The computer program product of claim 19 , wherein:
the third evaluation rule further comprises:
assigning, based on the context data, a first weighting value to a first answer category of a set of answer categories,
assigning, based on the context data, a second weighting value to a second answer category of the set of answer categories, and
calculating, by a statistical algorithm using the first weighting value and the second weighting value, an aggregate score; and
generating the sequence evaluation score for the first answer sequence includes assigning, to the first answer sequence, the aggregate score as the sequence evaluation score.

Assignees

• IBM

Inventors

• Barker Kevin S
• Eggebraaten Thomas J
• Megerian Mark G

Classifications

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06F16/24522 Primary

  Translation of natural language queries to structured queries · CPC title

• G06F16/3334

  Selection or weighting of terms from queries, including natural language queries · CPC title

• G06F40/30

  Semantic analysis · CPC title

• G06F16/24578

  using ranking · CPC title