Topic based classification and pattern identification in patents
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
ML can inform policy for accelerated materials science; previous work has applied natural language processing to patent data to understand the solar panel innovation process.
“ML can inform policy for accelerated materials science; for instance, previous work has applied natural language processing to patent data to understand the solar panel innovation process [813].”
From Tackling climate change with machine learning (2023) · cites this paper as [813]
The citation lists haven’t been fetched yet
References 77 · Cited by 116
- Authors
- Venugopalan, S., & Rai, V.
- Affiliations
- The University of Texas at Austin (US)
- Corresponding author
- Venugopalan, Subhashini
- Venue
- Technological Forecasting and Social Change
- Publisher
- Elsevier BV
- Published
- 2015-05
- Volume
- 94
- Pages
- 236-250
- ISSN
- 0040-1625 (ISSN-L)
- OpenAlex
- W2083776263
- Cited by
- 116
- References
- 77
- Citations by year
- 2026: 7 · 2025: 7 · 2024: 5 · 2023: 13 · 2022: 13 · 2021: 16 · 2020: 14 · 2019: 17 · 2018: 9 · 2017: 9 · 2016: 5 · 2015: 1
- FWCI
- 10.56
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Technological Forecasting and Social Change (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Intellectual Property and Patents
- Social Sciences › General Social Sciences › Computational and Text Analysis Methods
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Keywords
- patent classification, topic modeling, photovoltaics, patent citation networks, linguistic features, technology convergence, geography of innovation, knowledge flows, patent text analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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