Intellectual Property Technology Forecasting and Trends
3 patents in this list
Updated:
Patent and research literature databases now exceed 100 million documents, with over 3 million new patent applications filed annually worldwide. This vast corpus of technical documentation, combined with financial data, research papers, and market signals, creates an unprecedented opportunity to map and forecast technological change—but also presents substantial analytical challenges.
The core challenge lies in extracting meaningful innovation patterns and predictions from heterogeneous data sources while accounting for varying documentation practices across industries, organizations, and jurisdictions.
This page brings together solutions from recent research—including machine learning approaches for capability diagnosis, hybrid models combining patent and financial indicators, and automated systems for strategic technology reporting. These and other approaches focus on delivering actionable intelligence for R&D strategy, competitive analysis, and investment decisions.
1. Company-Level Innovation Prediction Using Machine Learning on Financial, News, Social Media, and Patent Data
KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY, 2023
Predicting future innovation at the company level based on big data and predictive analysis using machine learning techniques that explore the usefulness of company financial data, newspaper articles, social media data, and patent indicators.
2. Method for Analyzing Technology Capabilities Using Patent and Research Paper Data with Machine Learning Models
Jonghak OH, 2022
Diagnosing and predicting the science and technology capabilities of countries and companies using patent and research paper data. The method involves collecting patent and paper data for a technology, calculating variables from the data for each country or company, generating diagnosis models using machine learning, and using the models to diagnose and predict technology strengths and weaknesses.
3. System for Indexing and Analyzing Research and Patent Documents with Topic Overlap Quantification and Predictive Classification
Tata Consultancy Services Limited, 2018
Analyzing research literature to provide insights and reports for strategic decision-making. It involves indexing patent and research documents, determining topics, finding common phrases, quantifying topic overlap between patents and research, predicting patent classes, and generating customized reports for users based on their roles. The reports help identify emerging research, measure commercialization, and predict exploitable areas.
These technologies assess technological capabilities, forecast future advances, and aid in strategic decision-making by utilizing big data, machine learning, and sophisticated data analysis tools. Businesses are better equipped to deal with the complexity of IP protection and make educated judgments by utilizing such technologies and remaining up to date on developing trends.
