How Artificial Intelligence Can Simplify Patent Searching

The process of finding relevant patent documents and analyzing them can be extremely time-consuming, especially when done manually. However, Artificial Intelligence (AI) can significantly enhance the efficiency and accuracy of patent searching. AI includes Machine Learning (ML) and Natural Language Processing (NLP), which automate the searching process and provide relevant results.

Understanding Artificial Intelligence in Everyday Life

AI has become a ubiquitous presence in our daily lives. Have you ever noticed how your YouTube feed always has fascinating videos to offer? Or, how Google Assistant and Alexa can control your home as precisely as a butler? These are just a few examples of AI in action. AI is essentially a computer program that seeks to learn, much like how we observe and absorb our environment.

AIPatent Searching: A Closer Look

What is Patent Searching?

Patent searching involves searching through existing patents and publicly available documents to establish the novelty of an invention. This can include a wide range of items such as technical concepts, machines, algorithms, structures, compositions, designs, etc. Additionally, this search helps to determine if any granted patents were previously disclosed and, thus, challenge the validity of the granted claims.

The Role of AI in Patent Searching

The number of IP assets being filed globally has been steadily increasing. According to the World Intellectual Property Organization (WIPO), there was a 5.2% growth in patent filings between 2018 and 2019, and a 21.8% growth in utility model applications over the same period. As a result, finding relevant information in this vast amount of data becomes increasingly difficult and time-consuming.

AI can enhance patent searching and help save time, cost, and effort. While performing patent searches, AI can provide high accuracy and impeccable quality in a short turnaround time. Here’s how AI can make the process easier:

Cohesive Approach Through Effective Reuse of Knowledge

Deep Learning (DL) and Neural Networks (NN) not only automate the process of searching through massive volumes of information but also learn, store, and use previously analyzed data to improve overall search accuracy. Today's research is focused on using deep learning and neural networks for classifying or categorizing patents and finding similar patents. Natural Language Processing (NLP) is also employed to suggest contextually relevant keywords and their synonyms, leading to improved concordance between available knowledge and the documents users wish to search for.

AI tools can also help derive insights into the strengths and weaknesses of a technology segment in certain geographies by cross-referencing with IP data and delivering an instant overview of the domain.

Advanced AI-Based Patent Searching Tools

Various tools are available for patent searching, and each has unique features. Some tools not only provide a list of results based on AI similarity algorithms but also rank them based on the level of contextual similarity with the target invention. Some allow for more meaningful citation analysis, and a few allow searching for similar patents in the context of multiple target patents when the analysis requires identifying scattered concepts depicted in two known patents in a single prior art.

For example, if you believe one of the target patents is more important, you can adjust their respective weights, and the query results will be affected accordingly. AI tools are designed to increase analysis efficiency for users. For instance, tools like Ambercite remember the patents you have already reviewed, so you do not need to review them again.

Enhancing Analysis with AI

AI tools have a huge appetite for learning, much like an infant, waiting for us to train them. Amplified AI automatically learns with you as you analyze the results identified by the AI engine. Most AI tools have adaptive intelligence that grows their understanding and familiarity with a technology as you conduct more searches.

Modern IP professionals have access to various patent databases and tools that provide accurate patent search results. Examples include Ambercite, Amplified AI, Dorothy AI, and Resolute AI. These tools operate on AI to provide analysis and high-performance searching. With improved algorithms, IP professionals are now equipped with better decision-making tools and can effectively reach conclusions through their own analysis and interpretation of AI-recommended results.

Conclusion

The advent of the digital era has led to rapid transformations in numerous industries and sectors, with AI being one of the key digital technologies that has heavily impacted various industries. With digitalization and the accumulation of patent big data, AI has progressed rapidly in the IP industry. Though it still has a long way to match the multi-dimensions of human intelligence, it has allowed IP professionals to focus more on strategic tasks and utilize all the data around them in a structured and intelligent manner.

Keywords: Artificial Intelligence, Patent Search, Natural Language Processing