TEXTOIR: An Integrated and Visualized Platform for Text Open Intent Recognition
This platform addresses the need for a comprehensive tool in natural language processing to identify known intents and discover open intents, though it is incremental as it integrates existing methods into a unified framework.
The researchers tackled the problem of text open intent recognition by developing TEXTOIR, an integrated and visualized platform that combines open intent detection and discovery modules, resulting in a tool that provides state-of-the-art algorithms, benchmark datasets, and visualized interfaces for management and analysis.
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 (Toolkit code: https://github.com/thuiar/TEXTOIR), and designs a framework to implement a complete process to both identify known intents and discover open intents (Demo code: https://github.com/thuiar/TEXTOIR-DEMO).