The discovery of new intent categories from user utterances is a crucial task in expanding
agent skills. The key lies in how to efficiently solicit semantic evidence from utterances and …

Satisfaction evaluation provides valuable support for procurement decisions and product
improvement on e-commerce platforms. As an important task of satisfaction evaluation …

Document representation is the basis of language modeling. Its goal is to turn natural
language text that flows into a structured form that can be stored and processed by a …

Incomplete multi-view clustering (IMVC) is a critical task in real-world applications, where
missing data in some views can severely limit the ability to leverage complementary …

Class imbalance is a common problem in deep learning that severely degrades
performance. In federated learning (FL), it is a critical factor contributing to non-identically …

Empathetic response generation necessitates the integration of emotional and intentional
dynamics to foster meaningful interactions. Existing research either neglects the intricate …

Recent dialogue systems rely on turn-based spoken interactions, requiring accurate
Automatic Speech Recognition (ASR). Errors in ASR can significantly impact downstream …

This study introduces the Semantic Textual Similarity Pseudo-Label Semi-Supervised
Clustering (STSPL-SSC) framework. The STSPL-SSC framework is designed to tackle the …

Contrastive learning has gained significant attention in short text clustering, yet it has an
inherent drawback of mistakenly identifying samples from the same category as negatives …

Short text clustering has gained significant attention in the data mining community. However,
the limited valuable information contained in short texts often leads to low-discriminative …