Unbiased evaluation of ranking algorithms applied to the Chinese green patents citation network

As a phased achievement of technological innovation, patent analysis holds extraordinary research significance. By constructing patent citation networks, scholars have proposed various centrality algorithms (such as citation count, PageRank, LeaderRank, etc.) for evaluating the quality and influence...

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Bibliographic Details
Published in:Scientometrics 2024, Vol.129 (6), p.2999-3021
Main Authors: Liu, Xipeng, Li, Xinmiao
Format: Article
Language:English
Subjects:
Algorithms
Computer Science
Indicators
Information Storage and Retrieval
Library Science
Measurement methods
Performance evaluation
Ranking
Search algorithms
Technological change
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Summary:As a phased achievement of technological innovation, patent analysis holds extraordinary research significance. By constructing patent citation networks, scholars have proposed various centrality algorithms (such as citation count, PageRank, LeaderRank, etc.) for evaluating the quality and influence of patents. However, these centrality algorithms suffer from age bias, which means these algorithms are more inclined to obtain higher rankings for older patents, thus losing fairness to younger patents. Additionally, the selection of algorithm performance evaluation indicators is crucial. If the indicators are not chosen appropriately, the results may be affected. Therefore, based on the background of Chinese green patents, this paper develops an unbiased evaluation ranking algorithm to identify significant Chinese green patents earlier. The results demonstrate that the combination of the rescaled method and the AttriRank algorithm can effectively obtain the importance of patents, and provide a systematic and reasonable evaluation method for measuring patent value.
ISSN:0138-9130
1588-2861
DOI:10.1007/s11192-024-05023-1