Multi-Granularity Open Intent Classification via Adaptive Granular-Ball Decision Boundary

Open intent classification is critical for the development of dialogue systems, aiming to accurately classify known intents into their corresponding classes while identifying unknown intents. Prior boundary-based methods assumed known intents fit within compact spherical regions, focusing on coarse-grained representation and precise spherical decision boundaries. However, these assumptions are often violated in practical scenarios, making it difficult to distinguish known intent classes from unknowns using a single spherical boundary. To tackle these issues, we propose a Multi-granularity Open intent classification method via adaptive Granular-Ball decision boundary (MOGB). Our MOGB method consists of two modules: representation learning and decision boundary acquiring. To effectively represent the intent distribution, we design a hierarchical representation learning method. This involves iteratively alternating between adaptive granular-ball clustering and nearest sub-centroid classification to capture fine-grained semantic structures within known intent classes. Furthermore, multi-granularity decision boundaries are constructed for open intent classification by employing granular-balls with varying centroids and radii. Extensive experiments conducted on three public datasets demonstrate the effectiveness of our proposed method.

Authors

• Yanhua Li School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu 611130, China Engineering Research Center of Intelligent Finance, Ministry of Education, Chengdu 611130, China
• Xiaocao Ouyang School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu 611130, China Engineering Research Center of Intelligent Finance, Ministry of Education, Chengdu 611130, China
• Chaofan Pan School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu 611130, China Engineering Research Center of Intelligent Finance, Ministry of Education, Chengdu 611130, China
• Jie Zhang University of Bath
• Sen Zhao Key Laboratory of Big Data Intelligent Computing Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications, Chongqing, China Key Laboratory of Cyberspace Big Data Intelligent Security, Ministry of Education
• Shuyin Xia Key Laboratory of Big Data Intelligent Computing Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications, Chongqing, China Key Laboratory of Cyberspace Big Data Intelligent Security, Ministry of Education
• Xin Yang Dalian University of Technology
• Guoyin Wang National Center for Applied Mathematics in Chongqing, Chongqing Normal University, Chongqing 401331, China
• Tianrui Li School of Computing and Artificial Intelligence, Southwest Jiaotong University, China

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