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

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. Codes can be found at https://github.com/thuiar/TEXTOIR

Publication
Proceedings of the the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations (ACL-IJCNLP 2021, demo paper, CCF A)
Hua Xu
Hua Xu
Tenured Associate Professor, Editor-in-Chief of Intelligent Systems with Applications, Associate Editor of Expert Systems with Application, Ph.D Supervisor