Answering Student Queries with a Supervised Memory Conversational Agent
This paper describes a discussion-bot that provides answers to students’ questions about the Data Science master program at the University of Lyon 1. Based on a seq2seq architecture combined with a supervised memory module, the bot identifies the questioner’s interest and encodes relevant informatio...
Saved in:
| Main Authors: | Florian Baud, Alex Aussem |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
LibraryPress@UF
2023-05-01
|
| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Online Access: | https://journals.flvc.org/FLAIRS/article/view/133195 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
OLAP Techniques for Approximation and Mining Query Answering
by: Murtadaha Hamd, et al.
Published: (2010-12-01) -
An intelligent conversational agent for querying satellite manoeuvre detections: a case study
by: Wathsala Karunarathne, et al.
Published: (2025-06-01) -
TSQ: An Optimized Framework for Efficiently Answering Time Series Queries
by: Feifan Pu, et al.
Published: (2025-02-01) -
FGB-OPRAm: integrating fuzzy granular-ball and OPRAm for spatial query answering in uncertain environments
by: Bongjae Kwon, et al.
Published: (2025-08-01) -
Assessing the accuracy and readability of ChatGPT-4 and Gemini in answering oral cancer queries—an exploratory study
by: Márcio Diniz-Freitas, et al.
Published: (2024-11-01)