Segmenting Electronic Theses and Dissertations By Chapters

Electronic theses and dissertations (ETDs) are structured documents in which chapters are major components. There is a lack of any repository that contains chapter boundary details alongside these structured documents. Revealing these details of the documents can help increase accessibility. This research explores the manipulation of ETDs marked up using LaTeX to generate chapter boundaries. We use this to create a data set of 1,459 ETDs and their chapter boundaries. Additionally, for the task of automatic segmentation of unseen documents, we prototype three deep learning models that are trained using this data set. We hope to encourage researchers to incorporate LaTeX manipulation techniques to create similar data sets.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Science and Applications

Department dc:contributor.department

Computer Science and Applications

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2023

Author dc:creator

• Manzoor, Javaid Akbar

Chair dc:contributor.committeechair

• Fox, Edward A.

Committee members dc:contributor.committeemember

• Wu, Jian
• Heath, Lenwood S.

• segmentation
• deep learning
• natural language processing
• ETD
• digital libraries

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:35736

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/113246