Analysis of the effect of data properties in automated patent classification
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DOI: 10.1007/s11192-019-03246-1
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References listed on IDEAS
- Krier, Marc & Zaccà, Francesco, 2002. "Automatic categorisation applications at the European patent office," World Patent Information, Elsevier, vol. 24(3), pages 187-196, September.
- Sam Arts & Bruno Cassiman & Juan Carlos Gomez, 2018.
"Text matching to measure patent similarity,"
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Cited by:
- Cinthia M. Souza & Magali R. G. Meireles & Paulo E. M. Almeida, 2021. "A comparative study of abstractive and extractive summarization techniques to label subgroups on patent dataset," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 135-156, January.
- Choi, Seokkyu & Lee, Hyeonju & Park, Eunjeong & Choi, Sungchul, 2022. "Deep learning for patent landscaping using transformer and graph embedding," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
- Arousha Haghighian Roudsari & Jafar Afshar & Wookey Lee & Suan Lee, 2022. "PatentNet: multi-label classification of patent documents using deep learning based language understanding," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 207-231, January.
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Keywords
Patent classification; Hierarchical classification; Multilabel classification; Document representation; Supervised learning; IPC;All these keywords.
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