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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 2636 of 36 papers

TitleStatusHype
ClusterDataSplit: Exploring Challenging Clustering-Based Data Splits for Model Performance EvaluationCode0
Deep learning-based citation recommendation system for patents0
A Convolutional Neural Network-based Patent Image Retrieval Method for Design Ideation0
BERT-CNN: a Hierarchical Patent Classifier Based on a Pre-Trained Language Model0
A Label Informative Wide \& Deep Classifier for Patents and Papers0
PatentBERT: Patent Classification with Fine-Tuning a pre-trained BERT ModelCode0
Universal Language Model Fine-tuning for Patent Classification0
Classifying Patent Applications with Ensemble Methods0
Long-run dynamics of the U.S. patent classification system0
Filtering Patent Maps for Visualization of Diversification Paths of Inventors and Organizations0
Text Representations for Patent Classification0
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