A Survey on Sentence Embedding Models Performance for Patent Analysis

1 code implementation • 28 Apr 2022 • Hamid Bekamiri, Daniel S. Hain, Roman Jurowetzki

Therefore, in this study, we provide an overview of the accuracy of these algorithms based on patent classification performance and propose a standard library and dataset for assessing the accuracy of embeddings models based on PatentSBERTa approach.

Sentence Sentence Embedding +2

PatentSBERTa: A Deep NLP based Hybrid Model for Patent Distance and Classification using Augmented SBERT

2 code implementations • 22 Mar 2021 • Hamid Bekamiri, Daniel S. Hain, Roman Jurowetzki

This study provides an efficient approach for using text data to calculate patent-to-patent (p2p) technological similarity, and presents a hybrid framework for leveraging the resulting p2p similarity for applications such as semantic search and automated patent classification.

Classification General Classification +5

An evolutionary view on the emergence of Artificial Intelligence

1 code implementation • 30 Jan 2021 • Matheus E. Leusin, Bjoern Jindra, Daniel S. Hain

At the country level, we find that the US and Japan have been increasing the overall relatedness of their innovations.