TEXTOIR: An Integrated and Visualized Platform for Text Open Intent Recognition

Hanlei Zhang, Xiaoteng Li, Hua Xu, Panpan Zhang, Kang Zhao, Kai Gao

Abstract
TEXTOIR is the first integrated and visualized platform for text open intent recognition. It is composed of two main modules: open intent detection and open intent discovery. Each module integrates most of the state-of-the-art algorithms and benchmark intent datasets. It also contains an overall framework connecting the two modules in a pipeline scheme. In addition, this platform has visualized tools for data and model management, training, evaluation and analysis of the performance from different aspects. TEXTOIR provides useful toolkits and convenient visualized interfaces for each sub-module, and designs a framework to implement a complete process to both identify known intents and discover open intents.
Anthology ID:
2021.acl-demo.20
Volume:
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations
Month:
August
Year:
2021
Address:
Online
Editors:
Heng Ji, Jong C. Park, Rui Xia
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
167–174
Language:
URL:
https://aclanthology.org/2021.acl-demo.20
DOI:
10.18653/v1/2021.acl-demo.20
Bibkey:
Cite (ACL):
Hanlei Zhang, Xiaoteng Li, Hua Xu, Panpan Zhang, Kang Zhao, and Kai Gao. 2021. TEXTOIR: An Integrated and Visualized Platform for Text Open Intent Recognition. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations, pages 167–174, Online. Association for Computational Linguistics.
Cite (Informal):
TEXTOIR: An Integrated and Visualized Platform for Text Open Intent Recognition (Zhang et al., ACL-IJCNLP 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingest-2024-clasp/2021.acl-demo.20.pdf
Video:
 https://preview.aclanthology.org/ingest-2024-clasp/2021.acl-demo.20.mp4
Code
 thuiar/textoir +  additional community code
Data
SNIPS
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