Enhancing Unsupervised Keyword Extraction in Academic Papers through Integrating Highlights with Abstract
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. To investigate the impact of incorporating highlights into unsupervised keyword extraction, we evaluate three input scenarios: using only the abstract, the highlights, and a co...
| Authors | Yi Xiang, Chengzhi Zhang |
|---|---|
| Primary category | cs.IR |
| Published | 21 April 2026 |
| Last updated at source | 21 April 2026 |
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