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[期刊论文][Posters]
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Measuring Unequal Knowledge Distance by Network Embedding and Multiple Relationships
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作 者：
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Keye Wu;Lele Kang;Ziyue Xie;Jia Tina Du;Jianjun Sun;
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出版年：2023
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页 码：1188 - 1190
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出版社：John Wiley & Sons, Inc.
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摘 要：
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Knowledge distance, representing the dissimilarity between different knowledge units, has been considered as an important dimension of recombination novelty and technological innovation. Previous measurements merely rely on the citation relationship and ignore their directions and weights. To fill this gap, this study proposes a new measurement which not only captures the unequal citation relationship but also integrates multiple information to depict knowledge distance. The results show that our method can accurately portray the knowledge distance in both scientific areas and technical fields.
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关键字：
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Knowledge distance;Link prediction;Multiple relationship;Network embedding;Network visualization
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所属期刊
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ISSN: 2373-9231
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来自：John Wiley & Sons, Inc.
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