Enhancing Unsupervised Keyword Extraction in Academic Papers through Integrating Highlights with Abstract

ArXi:2604.19505v1 Announce Type: cross Automatic keyword extraction from academic papers is a key area of interest in natural language processing and information retrieval. Although previous research has mainly focused on utilizing abstract and references for keyword extraction, this paper focuses on the highlights section - a summary describing the key findings and contributions, offering readers a quick overview of the research. Our observations indicate that highlights contain valuable keyword information that can effectively complement the abstract.