Problem
Research questions and friction points this paper is trying to address.
novelty
scientific papers
knowledge units
relationships
evaluation
Measuring the Novelty of Biomedical Papers Using the Latent Distances between Knowledge Units
🤖 AI Summary
本文通过引入网络、语义和层级三种知识单元间的关系来衡量生物医学论文的新颖性，解决了现有方法仅关注共现关系导致评估不准确的问题。
📝 Abstract
Measuring the novelty of scientific papers is a central concern in research evaluation and scientometrics. From a recombination perspective, prior studies have largely focused on the co-occurrence of knowledge units to assess the novelty of scientific papers. However, these studies often overlook other relationships between knowledge units. This narrow view may result in inaccurate or incomplete evaluations of novelty for scientific papers. To fill this gap, this study introduces a comprehensive novelty measurement that incorporates three types of relationships between knowledge units: network, semantic, and hierarchical. These relationships are used to quantify the latent distances among knowledge units. Using a dataset of 142,036 articles published in PLoS ONE and a validation dataset from the H1 Connect platform, our results demonstrate that (1) each relationship type captures distinct latent distances between MeSH terms; (2) compared to the widely used indicators proposed by Uzzi et al. (2013), our measures show stronger alignment with peer judgements; and (3) combining all three distance metrics yields more effective identification of novel papers than using any single perspective alone.
Innovation
Methods, ideas, or system contributions that make the work stand out.
latent distances
knowledge units
novelty measurement
comprehensive evaluation
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