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PatentSBERTa

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sentence-transformers

feature-extraction

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HamidBekam commited on Mar 31, 2022

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 PatentSBERTa: A Deep NLP based Hybrid Model for Patent Distance and Classification using Augmented SBERT
-Hamid Bekamiri*, Daniel S. Hain, Roman Jurowetzki
-*Corresponding author for this work
-The IKE Research GroupThe Faculty of Social Sciences and HumanitiesAalborg University Business SchoolAI for the PeopleCluster for Research on Innovation and Development
-Research output: Contribution to journal › Journal article › Research › peer-review
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.

 PatentSBERTa: A Deep NLP based Hybrid Model for Patent Distance and Classification using Augmented SBERT
+The IKE Research GroupThe Faculty of Social Sciences and HumanitiesAalborg University Business School, AI for the People, Cluster for Research on Innovation and Development
 This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.