How is AI revolutionizing Patent Search?

Artificial Intelligence (AI) is a wide topic that has infiltrated our environment subtly and beneficially. Although all technical breakthroughs have a significant impact on human existence, AI goes beyond just altering lives. It aspires to comprehend and duplicate the entire fabric of cognition and reality. 

 

In its most basic form, AI is nothing more than a computer programme that seeks to learn. AI, like humans, watches and absorbs its environment, and learns from the facts it is provided. 

 

However, with the progress of AI technologies, dependence on computer systems to make certain judgments inside IP sectors has succeeded in causing trouble and can outwit the most promising IP search strategies. The technical adaptable IP departments are devoting most of their time to making decisions obtained from the results or insights supplied by machines. AI systems are playing a critical role in simplifying the typical IP search operation. 

 

AI technologies are supporting IP departments in lowering the effort spent on different IP searches/patent searches in different categories. But before jumping to the roles of AI in patent searching, let’s understand what exactly patent searching means.

 

 

What is Patent Search?

 

A patent search, also known as a patentability search, is the process of identifying if your idea is patentable. If a granted patent for the identical innovation already exists, any authority patent offices you appeal to (e.g., USPTO, JPO, CNIPA, etc.) will refuse your provisional patent. 

 

As a result, it's well worth checking the uniqueness of your innovation before investing too much time & expense in it. Performing your patent search is not tough; in fact, several inventors and businesses do their patent searches to save money. 

 

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Nonetheless, if you have the cash, hiring an expert or employing patent search software is often a good alternative for a more thorough search result. So, how does AI play a role in the patent search process? Let’s understand the connection between them.

 

 

AI and Patent Search

 

Worldwide, the quantity of IP assets filed is rapidly increasing. As per the WIPO 2019 analysis, patent filings increased by 5.2 percent between 2018 and 2019, while utility model applications increased by 21.8 percent between 2018 and 2019. This increased trend of filings has lasted over two decades.

 

As a result, IP resources have increased year after year, and locating meaningful information in this large dataset is getting more complex and time-intensive. With an expanding number of patent data, manually identifying relevant data and analyzing previous arts is time-consuming, especially if clarity and consistency are desired. 

 

AI can help reduce the time, money, and effort while looking for patents. When doing patent searches, AI gives great accuracy and superior quality promptly.

 

Coherent strategy based on optimal knowledge reuse

 

Deep learning and neural networks are being utilised in research today to classify or categorise patents and locate comparable patents. Natural language processing (NLP) is also used to recommend keywords and synonyms that are context-sensitive. 

 

(Since we mentioned NLP, you can take a look at the Top 10 NLP Trends in 2021?)

 

This results in better alignment between accessible information and content that users wish to look for. Through cross-referencing with IP data and providing a rapid glimpse of the domain, AI may also assist in drawing insight into the strengths and limitations of a technological sector in certain locations.

 

What Happens When AI-Powered Patent Search Tools Are Used?

 

There are several tools accessible to searchers, each with its own set of characteristics that make it distinctive in its own right. Some technologies not only present a list of results based on AI similarity algorithms but also rank/score them depending on the amount of contextual similarity with the target innovation. 

 

Some allow for more relevant citation analysis, and a couple allows you to search for related patents in the context of several target patents where the analysis needs the scattering notion (depicted in two previously known patents) to be discovered in a single patent claim.

 

 

AI Tools Empowering Patent Search

 

There are also AI-based search engines that locate similar previous work by focusing on the desired notion rather than just the keywords. They employ cutting-edge data science to analyse documents and uncover the connecting threads inside them.

 

AI tools, like infants, have a voracious thirst for learning and are just waiting for us to instruct them. Augmented AI learns alongside you as you examine the outcomes provided by the AI engine. 

 

Many AI tools have reactive intelligence, which allows them to develop their conscience and knowledge with advancements as we make more and more searches.

 

 

Improvement of Patent Databases Using AI

 

IP professionals now have full rights to a variety of patent databases and tools that deliver reliable patent search results. Many patent databases, such as Ambercite, Amplified AI, Dorothy AI, Resolute AI, and others, rely on artificial intelligence to offer analysis and slightly elevated searching. 

 

IP professionals now have stronger decision making tools thanks to updated algorithms, and they can successfully draw conclusions based on their interpretation and analysis of the Intelligence outcomes.

 

 

Factors Influencing the Use of AI in Patent Search

 

Many dependent aspects characterise the level of performance of AI in patent search, as well as in all other use cases:

 

• The broader the data set, the greater the likelihood of success or, more importantly, value.

 

• The predicted accuracy (predicted recall + expected accuracy) should be modest so low-auto solutions continue to be incapable of doing high recall/precise jobs.

 

• The more exploratory the use case, the more likely a fruitful outcome.

 

• AI assisting the analyst in his analysis process has the potential to add significant value.

 

 

Benefits of AI in Patent Search

 

AI technologies are making a huge impact in simplifying the typical IP search operation. AI technologies are supporting IP disciplines in lowering the time spent on various IP searches/patent search results.

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Benefits of AI in Patent Search

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Following are the eight primary points that explain the key Benefits of AI in a patent search.

 

1. Novelty Testing Digitization

 

Patentability searches are conducted in-house or outsourced by IP departments on discoveries shared by R&D departments. 

 

Using NLP, Machine Learning, and sentiment analysis, AI technologies are revolutionising the traditional method of inventive step searches. Experts first submit innovations to AI engines to acquire Novelty Updates and Simulations to determine their probable future stages.

 

• Reports on Novelty - AI includes evidence of overlap with earlier work as well as unique components.

 

• Visualization - Competitive prevention in the relevant technology.

 

 

2. Optimizing Patent Performance

 

IP departments are now taking a more concentrated strategy to file IP; it is much more concentrated and with explicit knowledge of where fulfilment is at, and ONLY a specified set of patent applications are being carried forward- the culling procedure in real-time and quicker utilising AI.

 

 

3. Actions to abandon, maintain, or out-license

 

Competitive analysis tracking is a continual procedure that necessitates repeated searches after a set time. AI algorithms are handy, and they may replace human, time-consuming searches with an automatic warning system.

 

 

4. Identifying the Most Important Patents in a Portfolio

 

Finding essential patents in a portfolio is a time-consuming activity where automation may help by evaluating established factors. In addition, by comparing competition and market intelligence with Patent data, AI algorithms may replicate the behaviour of an expertise searcher.

 

 

5. Invalidity Searching Automation

 

Automation of Invalidation Searches saves around 60% of the time. Using NLP and Machine Learning technology, AI can analyse the meaning of text data and match similarities between distinct texts.

 

(Speaking of Machine learning, learn the Basics of Machine Learning)

 

 

6. Using advanced technologies to disseminate information in a systematic manner

 

Implementing AI-based solutions can tackle the challenge of keeping global offices/different departments up to date on new technology and upgrades. Some organisations' IP departments are collaborating with AI providers to set up a Single Repository Alert system for focused alerts and synchronising warnings across worldwide offices.

 

 

7. Automation in Independent Counseling

 

IP departments provide several inquiries to inventors to have a better understanding of their discoveries. AI technology may help IP departments obtain system reports and observations in near real-time, allowing them to ask focused inquiries and derive innovative features of the innovation in even less time.

 

 

8. Innovation Automation

 

AI can comprehend user technology and offer fresh ideas. It aids in defining the scope and extra implementations for a better draught of a system.

 

 

Conclusion

 

Digitalization has resulted in the fast development of several businesses and sectors. Artificial intelligence (AI) is a modern technology that has had a significant influence on a variety of sectors. 

 

With the digital revolution and the formation of patent big data, AI is a suitable processing concept due to better computer functionality to complete tasks such as visual perception, text processing, judgement, contextual matchmaking, NLP, language translation, and so on. 

 

AI has advanced rapidly in the IP sector over the last few years. Though technology is still a long way from matching the multidimensionality of human intelligence, it has enabled IP professionals to switch their emphasis to more strategic duties and make more organised and intelligent use of those data surrounding them.