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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

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Showing 26–36 of 36 papers

TitleStatusHype
Research on feature fusion and multimodal patent text based on graph attention network—0
Retrouver l'inventeur-auteur : la levée d'homonymies d'autorat entre les brevets et les publications scientifiques—0
Semantic Similarity Matching for Patent Documents Using Ensemble BERT-related Model and Novel Text Processing Method—0
Solar cell patent classification method based on keyword extraction and deep neural network—0
Technical Progress Analysis Using a Dynamic Topic Model for Technical Terms to Revise Patent Classification Codes—0
Unveiling Black-boxes: Explainable Deep Learning Models for Patent Classification—0
Text Representations for Patent Classification—0
The evolving boundary of green technology—0
Automated Single-Label Patent Classification using Ensemble Classifiers—0
BERT-CNN: a Hierarchical Patent Classifier Based on a Pre-Trained Language Model—0
Classifying Patent Applications with Ensemble Methods—0
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