This is a curated list of resources for patent data mining, information retrieval from patent databases, patent data sources, etc.
- USPTO API
- USPTO PatentsView API
- Espacenet Open Patent Services
- Google Patents Public Datasets
- PQAI API
- Lens API
- PatentMatch: A Dataset for Matching Patent Claims & Prior Art
- Patent Classification Gold Standard (Qubit Dataset)
- United States Patent and Trademark Office (USPTO)
- Eurpoean Patent Office (EPO)
- Singapore Patent Office (IPOS)
- IP Australia
- United Kingdom IP Office
- Indian Patent Office
- Korean Patent Office
- World Intellectual Property Organization (WIPO)
- Japan Patent Office (JPO)
- China National Intellectual Property Administration
- Google Patents
- Lens
- PQAI
- Free Patents Online (FPO)
- Espacenet
- PATENTSCOPE
- JPlatPat (only Japanese patents)
- KIPRIS (only Korean patents)
- SIPO (only Chinese patents)
- PatentField
- IP Screener
- Derwent Innovation
- Patsnap
- PatentInspiration
- PatBase
- PatSeer
- PatentGuru
- Amplified AI
- IPRally
- InnovationQ Plus
- xlscout
- Orbit Intelligence
- Dorothy AI
- Similari
- Liu et al., 2023, Multi-task learning based high-value patent and standard-essential patent identification model
- Vowinckel and Hahnke, 2023, SEARCHFORMER: Semantic patent embeddings by siamese transformers for prior art search
- Siddharth and Luo, 2023, Embedding knowledge graph of patent metadata to measure knowledge proximity
- Siddharth and Luo, 2023, Towards Populating Generalizable Engineering Design Knowledge
- Geng and Wang, 2022, An SDN architecture for patent prior art search system based on phrase embedding
- Li et al., 2022, CoPatE: A Novel Contrastive Learning Framework for Patent Embeddings
- Lee et al., 2022, Multimodal Deep Learning for Patent Classification
- Lee et al. 2022, A Fast and Scalable Algorithm for Prior Art Search
- Nakamitsu et al. 2022, Analyzing the Structure of U.S. Patents Using Patent Families
- Choi et al., 2022, A two-stage deep learning-based system for patent citation recommendation
- Kim and Yoon, 2022, Multi-document summarization for patent documents based on generative adversarial network
- Bekamiri et al., 2022, A Survey on Sentence Embedding Models Performance for Patent Analysis
- Stamatis, 2022, End to End Neural Retrieval for Patent Prior Art Search
- Jeon et al., 2022, A doc2vec and local outlier factor approach to measuring the novelty of patents
- Roudsari et al., 2022, PatentNet: multi-label classification of patent documents using deep learning based language understanding
- Choi et al., 2022, Deep learning for patent landscaping using transformer and graph embedding
- Chi and Wang, 2022, Establish a patent risk prediction model for emerging technologies using deep learning and data augmentation
- Lo and Chu, 2021, Pre-trained Transformer-based Classification for Automated Patentability Examination
- Bekamiri et al., 2021, PatentSBERTa: A Deep NLP based Hybrid Model for Patent Distance and Classification using Augmented SBERT
- Pujari et al., 2021, A Multi-task Approach to Neural Multi-label Hierarchical Patent Classification Using Transformers
- Kumaravel and Sankaranarayanan, 2021, PQPS: Prior-Art Query-Based Patent Summarizer Using RBM and Bi-LSTM
- Setchi et al., 2021, Artificial intelligence for patent prior art searching
- Aristodemou, 2021, Identifying Valuable Patents: A Deep Learning Approach
- Krestel et al., 2021, A survey on deep learning for patent analysis
- Chikkamath et al., 2021, Patent Sentiment Analysis to Highlight Patent Paragraphs
- Yoo et al., 2021, Artificial Intelligence Technology analysis using Artificial Intelligence patent through Deep Learning model and vector space model
- Giczy et al., 2021, Identifying Artificial Intelligence (AI) Invention: A Novel AI Patent Dataset
- Freunek and Bodmer, 2021, BERT based freedom to operate patent analysis
- Freunek and Bodmer, 2021, BERT based patent novelty search by training claims to their own description
- Chikkamath et al., 2021, An Empirical Study on Patent Novelty Detection: A Novel Approach Using Machine Learning and Natural Language Processing
- Risch et al., 2021, PatentMatch: A Dataset for Matching Patent Claims & Prior Art
- Kang et al., 2020, Prior Art Search Using Multi-modal Embedding of Patent Documents
- Kang et al., 2020, Patent prior art search using deep learning language model
- Lee et al., 2020, Prior-Art Search and Reranking for Generated Patent Text
- Harris et al., 2020, Construction and evaluation of gold standards for patent classification—A case study on quantum computing
- Lu et al., 2020, Research on classification and similarity of patent citation based on deep learning
- Alderucci and Ashley, 2020, Using AI to Analyze Patent Claim Indefiniteness
- Sarica et al., 2019, Engineering Knowledge Graph for Keyword Discovery in Patent Search
- Sarica et al., 2019, TechNet: Technology Semantic Network based on Patent Data
- Abdelgawad et al., 2019, Optimizing Neural Networks for Patent Classification
- Helmers et al., 2019, Automating the search for a patent's prior-art with a full text similarity search
- Zhai et al., 2019, Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings
- Wang et al., 2019, A novelty detection patent mining approach for analyzing technological opportunities
- Lee and Hsiang, 2019, Patent Classification with Fine-Tuning a pre-trained BERT Model
- Andlauer, 2018, Automatic Pre-Search: An overview
- Kim et al., 2018, Patent document clustering with deep embeddings
- Lee et al., 2018, De-noising documents with a novelty detection method utilizing class vectors
- Li et al., 2018, DeepPatent: patent classification with convolutional neural networks and word embedding
- Hu et al., 2018, A Hierarchical Feature Extraction Model for Multi-label Mechanical Patent Classification
- Abood and Feltenberger, 2018, Automated Patent Landscaping
- Showkatramani et al., 2018, User Interface for Managing and Refining Related Patent Terms
- Tran and Kavuluru, 2017, Supervised approaches to assign cooperative patent classification (cpc) codes to patents
- Kravets et al., 2017, Patents Images Retrieval and Convolutional Network Training Dataset Quality Improvement
- Seneviratne et al., 2017, An initial study of anchor selection in patent link discovery
- Khode and Jambhorkar, 2017, A literature review on patent information retrieval techniques
- Krishna et al., 2016, Examiner Assisted Automated Patents Search
- Krishna et al., 2016, User Interface for Customizing Patents Search: An Exploratory Study
- Far et al., 2016, On term selection techniques for patent prior art search
- Bouadjenek et al., 2015, A study of query reformulation for patent prior art search with partial patent applications
- Lee et al., 2014, Novelty-focused patent mapping for technology opportunity analysis
- Gomez and Moens, 2014, A survey of automated hierarchical classification of patents
- Lin et al., 2014, A Hybrid Patent Prior Art Retrieval Approach Using Claim Structure and Description
- Geum et al., 2013, Identifying technological opportunities using the novelty detection technique: A case of laser technology in semiconductor manufacturing
- Wang et al., 2013, An Ontology-based Automatic Semantic Annotation Approach for Patent Document Retrieval in Product Innovation Design
- Krestel and Smith, 2013, Recommending patents based on latent topics
- Gerken et al., 2012, A new instrument for technology monitoring: novelty in patents measured by semantic patent analysis
- Pasche et al., 2012, Development of a text search engine for medicinal chemistry patents
- Teodoro et al., 2011, Automatic IPC Encoding and Novelty Tracking for Effective Patent Mining
- Khattak and Heyer, 2011, Significance of low frequent words in patent classification
- Cai et al., 2010, A KNN Research Paper Classification Method Based on Shared Nearest Neighbor
- Urbain and Frieder, 2010, Exploring contextual models in chemical patent search
- Bashir and Rauber, 2010, Improving retrievability of patents in prior-art search
- Takeuchi et al., 2004, Experiments on Patent Retrieval at NTCIR-4 Workshop