Abstract
Patents in the pharmaceutical field fulfil an important role as they contain details of the final product that is the culmination of years of research and possibly millions of dollars of investment. It is crucial that both patent producers and consumers are able to assess the novelty of such patents and perform basic processing on them. In this work, we review approaches in the literature in patent analysis and novelty assessment that range from basic digitisation to deep learning-based approaches including natural language processing, image processing and chemical structure extraction. We propose a system that automates the process of patent novelty assessment using Siamese neural networks for similarity detection. Our system showed promising results and has a potential to improve upon the current patent analysis methods, specifically in the pharmaceutical field, by not just focusing on the task from a Natural Language Processing perspective, but also, adding image analysis and adaptations for chemical structure extraction.
Original language | English |
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Title of host publication | Artificial Neural Networks in Pattern Recognition. ANNPR 2022 |
Editors | Neamat El Gayar, Edmondo Trentin, Mirco Ravanelli, Hazem Abbas |
Publisher | Springer |
Pages | 140-155 |
Number of pages | 16 |
ISBN (Electronic) | 9783031206504 |
ISBN (Print) | 9783031206498 |
DOIs | |
Publication status | Published - 2023 |
Event | 10th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition 2022 - Dubai, United Arab Emirates Duration: 24 Nov 2022 → 26 Nov 2022 https://annpr2022.com/ |
Publication series
Name | Lecture Notes in Computer Science |
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Volume | 13739 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 10th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition 2022 |
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Abbreviated title | ANNPR 2022 |
Country/Territory | United Arab Emirates |
City | Dubai |
Period | 24/11/22 → 26/11/22 |
Internet address |
Keywords
- Chemical structure extraction
- CNN
- Document analysis
- LSTM
- Optical character recognition
- Pharmaceutical patents
- Siamese neural networks
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science