Nguyen, Huy
(2018)
Context-aware Argument Mining and Its Applications in Education.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Context is crucial for identifying arguments and argumentative relations in text, but existing argument studies have not addressed context dependence adequately. In this thesis, we propose context-aware argument mining that makes use of contextual features extracted from writing topics and context sentences to improve state-of-the-art argument component and argumentative relation classifications. The effectiveness as well as generality of our proposed contextual features is proven through its application in different argument mining tasks in student essays. We further evaluate the applicability of our proposed argument mining models in automated persuasive essay scoring tasks.
Share
| Citation/Export: |
|
| Social Networking: |
|
Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
|
| Date: |
31 January 2018 |
| Date Type: |
Publication |
| Defense Date: |
14 April 2017 |
| Approval Date: |
31 January 2018 |
| Submission Date: |
5 November 2017 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
196 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Dietrich School of Arts and Sciences > Computer Science |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
argument mining, topic context, context segment, automated essay scoring |
| Date Deposited: |
31 Jan 2018 18:26 |
| Last Modified: |
31 Jan 2018 18:26 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/33316 |
Metrics
Monthly Views for the past 3 years
Plum Analytics
Actions (login required)
 |
View Item |
![[feed]](/images/feed-icon-32x32.png){kind=icon}