Computer Science > Computation and Language
[Submitted on 9 May 2021 (v1), last revised 2 Jul 2021 (this version, v2)]
Title:Improving Patent Mining and Relevance Classification using Transformers
View PDFAbstract:Patent analysis and mining are time-consuming and costly processes for companies, but nevertheless essential if they are willing to remain competitive. To face the overload induced by numerous patents, the idea is to automatically filter them, bringing only few to read to experts. This paper reports a successful application of fine-tuning and retraining on pre-trained deep Natural Language Processing models on patent classification. The solution that we propose combines several state-of-the-art treatments to achieve our goal - decrease the workload while preserving recall and precision metrics.
Submission history
From: Binbin Xu [view email][v1] Sun, 9 May 2021 17:57:55 UTC (312 KB)
[v2] Fri, 2 Jul 2021 13:09:29 UTC (103 KB)
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