Patent Clustering

Patent Clustering is a patent analysis method that groups patent documents into coherent categories based on similarities in technological content, citation patterns, or metadata, thereby enabling the identification of innovation trends, competitive landscapes, and technological domains.

88

Publications

3.4K

Citations

254

Authors

124

Institutions

Publications per year

2017–2026

35

Authors

254

  1. AJ
    Amy J.C. Trappey

    National Tsing Hua University, Taiwan

    7 publications · 204 citations

    7

    h-index

  2. CV
    Charles V. Trappey

    National Yang Ming Chiao Tung University, Taiwan

    7 publications · 204 citations

    7

    h-index

  3. SJ
    Sunghae Jun

    Cheongju University, South Korea

    4 publications · 208 citations

    4

    h-index

  4. DJ
    Dong‐Sik Jang

    Korea University, South Korea

    4 publications · 123 citations

    4

    h-index

  5. SP
    Sangsung Park

    Korea University, South Korea

    4 publications · 123 citations

    4

    h-index

1–5 of 254

Venues

  1. Sustainability

    10 publications · 268 citations

    10

    h-index

  2. Scientometrics

    8 publications · 294 citations

    8

    h-index

  3. Technology Analysis and Strategic Management

    5 publications · 136 citations

    5

    h-index

  4. Research Policy

    4 publications · 383 citations

    4

    h-index

  5. IEEE Transactions on Engineering Management

    4 publications · 202 citations

    3

    h-index

1–5