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Patent classification

Patent reviewers usually are responsible to classify the patent applications, i.e., they assign the design codes. This is time-consuming due to the numerous classification codes. For instance, the U.S. design patent system has 33 classes which are further divided into subclasses. Given that design patents include both titles and visual content, the goal of the experiment is patent classification by integrating titles, captions, and images. Although a single design patent can be associated with multiple design codes, we focus on the primary classification—solving the task as a multi-class classification problem.

Papers

Showing 110 of 36 papers

TitleStatusHype
PatentSBERTa: A Deep NLP based Hybrid Model for Patent Distance and Classification using Augmented SBERTCode1
IMPACT: A Large-scale Integrated Multimodal Patent Analysis and Creation Dataset for Design PatentsCode1
Extracting effective solutions hidden in large language models via generated comprehensive specialists: case studies in developing electronic devices0
DAPFAM: A Domain-Aware Patent Retrieval Dataset Aggregated at the Family Level0
Deep Learning for Technical Document Classification0
Automated Single-Label Patent Classification using Ensemble Classifiers0
Classifying Patent Applications with Ensemble Methods0
BERT-CNN: a Hierarchical Patent Classifier Based on a Pre-Trained Language Model0
A Convolutional Neural Network-based Patent Image Retrieval Method for Design Ideation0
A Label Informative Wide \& Deep Classifier for Patents and Papers0
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