[1903.05823] A Deep Patent Landscaping Model using Transformer and Graph Convolutional Network (2019)(About) a transformer encoder
for analyzing textual data present in patent documents
and a graph convolutional network for analyzing
A benchmarking dataset for patent landscaping
based on patent trends reports published by the
Korean Patent Office. Data acquisition using Google's BigQuery public datasets.
10% improvement comparing to Google’s proposed Automated Patent Landscaping.
Empirical analysis of the importance of features (text vs metadata, citations vs classification)