Analyzing and Navigating ETDs Using Topic Models

Authors

Aman Ahuja, Virginia Polytechnic Institute and State UniversityFollow
Chenyu Mao, Virginia Polytechnic Institute and State UniversityFollow
William Ingram, Virginia Polytechnic Institute and State UniversityFollow
Edward A. Fox, Virginia TechFollow

ORCID

Aman Ahuja - 0009-0002-8491-0193 Chenyu Mao - 0009-0006-4341-4344 William A. Ingram - 0000-0002-8307-8844 Edward A. Fox - 0000-0003-1447-6870

Abstract

Electronic theses and dissertations (ETDs) contain valuable knowledge that can be useful in a wide range of research areas. Accordingly, we are building electronic infrastructure leveraging advanced work on digital libraries, for discovering and accessing the knowledge buried in ETDs. In this paper we focus on our work to incorporate topic modeling into digital libraries for ETDs. We present ETD-Topics, a framework that extracts topics from a large text corpus in an unsupervised way. The representations learned from topic models can be useful for downstream tasks such as searching and/or browsing documents by topic, document recommendation, topic recommendation, and describing temporal topic trends (e.g., from the perspective of disciplines or universities).

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.

Recommended Citation

Ahuja, Aman; Mao, Chenyu; Ingram, William; and Fox, Edward A. (2024) "Analyzing and Navigating ETDs Using Topic Models," The Journal of Electronic Theses and Dissertations: Vol. 3, Article 4.
Available at: https://scholarworks.uaeu.ac.ae/j-etd/vol3/iss1/4