IP Library Granted Patent US 10,339,169
Granted Patent B2
US 10,339,169 · App. 15/259,520 · Granted Jul 2, 2019

Method and system for response evaluation of users from electronic documents

Inventors: Shourya Roy (Bangalore, IN); Deepali Semwal (Uttarakhand, IN); Raghuram Krishnapuram (Bangalore, IN)
Assignee: Conduent Business Services, LLC
G06F16/335G06F16/3329G06F16/34G09B7/02
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Quick Facts
Patent No.
US 10,339,169
App. No.
15/259,520
Granted
Jul 2, 2019
Kind
B2
Abstract

A method and a system for response evaluation of users from electronic documents are disclosed. In an embodiment, one or more questions and a first response pertaining to each of the one or more questions are extracted from one or more first electronic documents. Further, a second response pertaining to each of the one or more extracted questions and metadata are extracted from one or more second electronic documents. For the second response pertaining to each of the one or more extracted questions, a score is determined based on one or more similarity measures that correspond to a category of each of the one or more extracted questions. Thereafter, the response evaluation is rendered on a user interface displayed on a display screen. The response evaluation comprises at least the determined score for the second response pertaining to each of the one or more extracted questions.

Claims (53)

1. A method of operating a computer-assisted assessment system, the method comprising:

extracting, by a document processor, one or more examination questions and a first free-text response pertaining to each of the one or more examination questions from one or more first electronic documents received from an evaluator computing device associated with an evaluator over a communication network;

extracting, by the document processor, a second free-text response pertaining to each of the one or more extracted examination questions and metadata from one or more second electronic documents received from a subject computing device associated with a subject to be evaluated over the communication network, wherein the metadata comprises at least one subject identifier;

for the second free-text response pertaining to each of the one or more extracted examination questions:

determining, by a processor, a score and feedback based on one or more similarity measures associated with a category of each of the one or more extracted examination questions, wherein the one or more similarity measures comprise a lexical similarity measure, a syntactic similarity measure, a semantic similarity measure, or a vector space similarity measure, or a combination thereof, wherein:

the lexical similarity measure is associated with a disjunctive category, a concept completion category, a feature specification category, or a casual antecedent category, or a combination thereof;

the syntactic similarity measure is associated with a verification category, a quantification category, a definition category, an example category, a comparison category, an instrumental/procedural category, or an enablement category;

the semantic similarity measure is associated with the definition category, the comparison category, an interpretation category, a causal antecedent category, a casual consequence category, a goal orientation category, the enablement category, an expectational category, or a judgmental category, or a combination thereof; and

the vector space similarity measure is associated with a disjunctive category, the feature specification category, or both;

generating, by the processor, an evaluation report comprising the determined score and the feedback; and

rendering, by the processor, the evaluation report on a user interface displayed on a display screen of the evaluator computing device.

2. The method of claim 1 wherein the subject identifier comprises one or more of a name, a grade, a roll number, a class, and a section.

3. The method of claim 1 further comprising classifying, by the document processor, each of the one or more extracted examination questions in the one or more categories based on at least a type and content of the one or more extracted examination questions.

4. The method of claim 3 , wherein the one or more categories correspond to one or more of the verification category, the disjunctive category, the concept completion category, the feature specification category, the quantification category, the definition category, the example category, the comparison category, the interpretation category, the casual antecedent category, the casual consequence category, the goal orientation category, the instrumental/procedural category, the enablement category, the expectational category, and the judgmental category.

5. The method of claim 1 , wherein the lexical similarity measure is associated with the disjunctive category, the concept completion category, the feature specification category, and the casual antecedent category.

6. The method of claim 1 , wherein the syntactic similarity measure is associated with the verification category, the quantification category, the definition category, the example category, the comparison category, the instrumental/procedural category, and the enablement category.

7. The method of claim 1 , wherein the semantic similarity measure is associated with the definition category, the comparison category, the interpretation category, the casual antecedent category, the casual consequence category, the goal orientation category, the enablement category, the expectational category, and the judgmental category.

8. The method of claim 1 , wherein the vector space similarity measure is associated with the disjunctive category and the feature specification category.

9. The method of claim 1 further comprising receiving, by the processor, an updated score and an updated feedback, pertaining to the second free-text response, from the evaluator, when the determined score is less than a threshold score.

10. The method of claim 1 further comprising receiving, by the processor, an updated score and an updated feedback, pertaining to the second free-text response, from the evaluator, when the determined score is rebutted by the subject.

11. The method of claim 1 , wherein the evaluator is a teacher and the subject is a student.

12. The method of claim 1 , wherein the one or more similarity measures comprise the lexical similarity measure, the syntactic similarity measure, the semantic similarity measure, and the vector space similarity measure.

13. A computer-assisted assessment system, the system comprising:

a document processor configured to:

extract one or more examination questions and a first free-text response pertaining to each of the one or more examination questions from one or more first electronic documents received from an evaluator computing device associated with an evaluator over a communication network;

extract a second free-text response pertaining to each of the one or more extracted examination questions and metadata from one or more second electronic documents received from a subject computing device associated with a subject to be evaluated over the communication network, wherein the metadata comprises at least one subject identifier;

a processor configured to:

for the second free-text response pertaining to each of the one or more extracted examination questions:

determine a score and feedback based on one or more similarity measures associated with a category of each of the one or more extracted examination questions, wherein the one or more similarity measures comprise a lexical similarity measure, a syntactic similarity measure, a semantic similarity measure, or a vector space similarity measure, or a combination thereof, wherein:

the lexical similarity measure is associated with a disjunctive category, a concept completion category, a feature specification category, or a casual antecedent category, or a combination thereof;

the syntactic similarity measure is associated with a verification category, a quantification category, a definition category, an example category, a comparison category, an instrumental/procedural category, or an enablement category;

the semantic similarity measure is associated with the definition category, the comparison category, an interpretation category, a causal antecedent category, a casual consequence category, a goal orientation category, the enablement category, an expectational category, or a judgmental category, or a combination thereof; and

the vector space similarity measure is associated with a disjunctive category, the feature specification category, or both;

generate, by the processor, an evaluation report comprising the determined score and the feedback; and

render the evaluation report on a user interface displayed on a display screen of the evaluator computing device.

14. The system of claim 13 , wherein the document processor is further configured to classify each of the one or more extracted examination questions in one or more categories based on at least a type and content of the one or more extracted examination questions.

15. The system of claim 14 , wherein each of the one or more categories is associated with at least one of the one or more similarity measures, wherein the one or more similarity measures correspond to one or more of the lexical similarity measure, the syntactic similarity measure, the semantic similarity measure, and the vector space similarity measure.

16. The system of claim 13 , wherein the processor is further configured to receive an updated score and an updated feedback, pertaining to the second free-text response, from a first the evaluator, when the determined score is less than a threshold score.

17. The system of claim 13 , wherein the processor is further configured to receive an updated score and an updated feedback, pertaining to the second free-text response, from the evaluator, when the determined score is rebutted by the subject.

18. The system of claim 13 , wherein the evaluator is a teacher and the subject is a student.

19. The system of claim 13 , wherein the one or more similarity measures comprise the lexical similarity measure, the syntactic similarity measure, the semantic similarity measure, and the vector space similarity measure.

20. A computer program product for use with a computer-assisted assessment system, the computer program product comprising a non-transitory computer readable medium, wherein the non-transitory computer readable medium stores a computer program code for operating the computer-assisted assessment system, wherein the computer program code is executable by a processor in a server to:

extract one or more examination questions and a first free-text response pertaining to each of the one or more examination questions from one or more first electronic documents from an evaluator computing device associated with an evaluator over a communication network;

extract a second free-text response pertaining to each of the one or more extracted examination questions and metadata from one or more second electronic documents from a subject computing device associated with a subject to be evaluated over the communication network, wherein the metadata comprises at least one subject identifier;

for the second free-text response pertaining to each of the one or more extracted examination questions:

determine a score and feedback based on one or more similarity measures associated with a category of each of the one or more extracted examination questions, wherein the one or more similarity measures comprise a lexical similarity measure, a syntactic similarity measure, a semantic similarity measure, or a vector space similarity measure, or a combination thereof, wherein:

the lexical similarity measure is associated with a disjunctive category, a concept completion category, a feature specification category, or a casual antecedent category, or a combination thereof;

the syntactic similarity measure is associated with a verification category, a quantification category, a definition category, an example category, a comparison category, an instrumental/procedural category, or an enablement category;

the semantic similarity measure is associated with the definition category, the comparison category, an interpretation category, a causal antecedent category, a casual consequence category, a goal orientation category, the enablement category, an expectational category, or a judgmental category, or a combination thereof; and

the vector space similarity measure is associated with a disjunctive category, the feature specification category, or both;

generate, by the processor, an evaluation report comprising the determined score and the feedback; and

render the evaluation report on a user interface displayed on a display screen of the evaluator computing device.

21. The computer program product of claim 20 , wherein the evaluator is a teacher and the subject is a student.

Assignments (6)
SECURITY INTEREST Recorded Oct 19, 2021
From: CONDUENT BUSINESS SERVICES, LLC
To: U.S. BANK, NATIONAL ASSOCIATION
Reel/Frame 057969/0445 →
SECURITY INTEREST Recorded Oct 19, 2021
From: CONDUENT BUSINESS SERVICES, LLC
To: BANK OF AMERICA, N.A.
Reel/Frame 057970/0001 →
RELEASE OF SECURITY INTEREST Recorded Oct 18, 2021
From: JPMORGAN CHASE BANK, N.A.
To: CONDUENT BUSINESS SERVICES, LLC; CONDUENT STATE & LOCAL SOLUTIONS, INC.; CONDUENT TRANSPORT SOLUTIONS, INC.; ADVECTIS, INC.; CONDUENT COMMERCIAL SOLUTIONS, LLC; CONDUENT BUSINESS SOLUTIONS, LLC; CONDUENT CASUALTY CLAIMS SOLUTIONS, LLC; CONDUENT HEALTH ASSESSMENTS, LLC
Reel/Frame 057969/0180 →
SECURITY AGREEMENT Recorded Mar 19, 2020
From: CONDUENT BUSINESS SERVICES, LLC
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 052189/0698 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 28, 2017
From: XEROX CORPORATION
To: CONDUENT BUSINESS SERVICES, LLC
Reel/Frame 041542/0022 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 9, 2016
From: ROY, SHOURYA , ,; SEMWAL, DEEPALI , ,; KRISHNAPURAM, RAGHURAM , ,
To: XEROX CORPORATION
Reel/Frame 039680/0941 →
Continuity (1)
Related Publication 20180068016A1 · Mar 8, 2018