Patent Text Mining
Patent Text Mining is a computational analysis technique that extracts, processes, and interprets textual information from patent documents to uncover technical, legal, and competitive intelligence, distinguishing itself from general text mining by its focus on the unique structure, language, and semantic content of patent literature.
578
Publications
26.5K
Citations
1.4K
Authors
549
Institutions
Publications per year
2017–2026
244
Parents
578
1–5 of 578
1.4K
14
h-index
13
h-index
12
h-index
12
h-index
11
h-index
1–5 of 1.4K
549

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
15 h-index
23 publications
1.3K citations
National Tsing Hua University
Hsinchu, Taiwan
15 h-index
40 publications
2.1K citations
University of Bremen
Bremen, Germany
13 h-index
27 publications
1.5K citations

Dongguk University
Seoul, South Korea
11 h-index
25 publications
1.1K citations
Korea University
Seoul, South Korea
9 h-index
19 publications
703 citations
University of Tsukuba
Tsukuba, Japan
9 h-index
9 publications
347 citations
Pohang University of Science and Technology
Pohang, South Korea
9 h-index
18 publications
1.3K citations
Seoul National University
Seoul, South Korea
9 h-index
21 publications
2.5K citations
1–8 of 549
48 publications · 2.3K citations
28
h-index
56 publications · 2.5K citations
26
h-index
24 publications · 1.6K citations
23
h-index
22 publications · 1.8K citations
21
h-index
12 publications · 363 citations
12
h-index
1–5