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README.md
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Aalborg University Business School, AI: Growth-Lab
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https://www.sciencedirect.com/science/article/abs/pii/S0040162524003329
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Bekamiri, H., Hain, D. S., & Jurowetzki, R. (2024). PatentSBERTa: A deep NLP based hybrid model for patent distance and classification using augmented SBERT. Technological Forecasting and Social Change, 206, 123536.
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https://github.com/AI-Growth-Lab/PatentSBERTa
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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.
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<!--- Describe your model here -->
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## Usage (Sentence-Transformers)
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<!--- Describe where people can find more information -->
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Aalborg University Business School, AI: Growth-Lab
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https://www.sciencedirect.com/science/article/abs/pii/S0040162524003329
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https://github.com/AI-Growth-Lab/PatentSBERTa
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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.
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## Citing & Authors
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Bekamiri, H., Hain, D. S., & Jurowetzki, R. (2024). PatentSBERTa: A deep NLP based hybrid model for patent distance and classification using augmented SBERT. Technological Forecasting and Social Change, 206, 123536.
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<!--- Describe your model here -->
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## Usage (Sentence-Transformers)
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)
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```
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<!--- Describe where people can find more information -->
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