Efficient intent classification and entity recognition for university administrative services employing deep learning models

Efficient intent classification and entity recognition for university administrative services employing deep learning models

The design and implementation of a domain specific conversational agent requires efficient Natural Language Understanding (NLU). The task is harder when multiple languages have to be supported, and training datasets can be beneficial. This work focuses on the development of an intelligent system, an...

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Bibliographic Details
Main Authors: S. Rizou, A. Theofilatos, A. Paflioti, E. Pissari, I. Varlamis, G. Sarigiannidis, K.Ch. Chatzisavvas
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:Intelligent Systems with Applications
Subjects:
Named Entity Recognition
Intent Extraction
Natural Language Understanding
Deep Learning
LSTM networks
Transformer networks
Online Access:http://www.sciencedirect.com/science/article/pii/S2667305323000728

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http://www.sciencedirect.com/science/article/pii/S2667305323000728

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