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

TL;DR

TEXTOIR is a comprehensive platform that integrates state-of-the-art algorithms for open intent recognition, providing visualization tools for data management, model training, and performance analysis in a unified pipeline.

Contribution

It introduces the first integrated, visualized platform combining open intent detection and discovery with user-friendly interfaces and toolkit support.

Findings

Integrates multiple algorithms and datasets in a unified platform

Provides visualization tools for data, models, and performance analysis

Enables both intent detection and discovery in a seamless pipeline

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 (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).