Michael Cammarere
Cosmic Queries: NLP for User-Friendly Access to Gaia/EDR3 Data
Abstract:
Natural Language Processing (NLP) is an exciting field that has gained significant attention in the last few years due to its ability to extract meaningful information from text data. The potential applications to astronomy are particularly transformational. In this contribution, we focus on data from the Gaia Early Data Release 3 (EDR3) archive, which contains information on over 1.4 billion astronomical objects. We present a prototype interface which uses NLP to allow a user to interactively query and interact with Gaia/EDR3. We conclude by discussing the strengths and limitations of NLP for astronomical applications and future steps of this project.
Title
Cosmic Queries: NLP for User-Friendly Access to Gaia/EDR3 Data
Faculty Advisor
Dr. John Moustakas
Course
PHYS 472: Capstone Research ||
Presentation Type
Poster
Location
Table 60

