Bridging the Semantic Gap for Categorical Data Clustering via Large Language Models 事件

Bridging the Semantic Gap for Categorical Data Clustering via Large Language Models arXiv:2601.01162v3 Announce Type: replace-cross Abstract: Qualitative data are widespread in domains such as healthcare, marketing, and bioinformatics, where clustering offers a fundamental tool for pattern discovery. A core difficulty of qualitative-data clustering lies in measuring similarity among attribute values that carry no inherent ordering or distance. To recover such relationships, existing studies typ