GINopic: Topic Modeling with Graph Isomorphism Network

arXiv:2404.02115v1 Announce Type: cross
Abstract: Topic modeling is a widely used approach for analyzing and exploring large document collections. Recent research efforts have incorporated pre-trained contextualized language models, such as BERT embeddings, into topic modeling. However, they often neglect the intrinsic informational value conveyed by mutual dependencies between words. In this study, we introduce GINopic, a topic modeling framework based on graph isomorphism networks to capture the correlation between words. By conducting intrinsic (quantitative as well as qualitative) and extrinsic …

abstract arxiv bert cs.cl cs.lg dependencies document embeddings graph however intrinsic language language models modeling network research study topic modeling type value words