We explore a machine learning task, evidence recommendation (ER), the extraction of evidence from a source document to support an external claim. This task is an instance of the question answering machine learning task. We apply ER to academic publications because they cite other papers for the claims they make. Reading cited papers to corroborate claims is time-consuming and an automated ER tool could expedite it. Thus, we propose a methodology for collecting a dataset of academic papers and their references. We explore deep learning models for ER and achieve 77% accuracy with pairwise models and 75% pairwise accuracy with document-wise models.

Creator

• Lovering, Charles

Contributeurs

• Whitehill, Jacob Richard

Degree

• MS

Unit

• Computer Science

Publisher

• Worcester Polytechnic Institute

Language

• English

Identifier

• etd-042618-024433

Mot-clé

• information retrieval
• Machine Learning
• Deep Learning
• natural language processing

Advisor

• Whitehill, Jacob Richard

Defense date

• 2018-04-19

Year

• 2018

Date created

• 2018-04-26

Resource type

• Thesis

Rights statement

• In Copyright

Dernière modification

• 2023-12-05