Patent Search and Monitoring: Using Explainable AI

Artificial intelligence (AI) has fast become an integral component of our daily lives. Years ago, only humans could perform basic activities like chess and data sorting. However, with the introduction of AI technology into modern markets, these tasks can now be easily outsourced, saving time. Researchers are increasing their focus on AI technology in order to revolutionize how we perform complex processes. One of these involves patent search and monitoring, which is required to safeguard your company’s intellectual property from theft. Let us first define these concepts before drawing a link between AI and patent search. 

AI – An Overview 

AI is a technological invention that mimics human intelligence and performs tasks that humans would normally perform. The world first heard about this technology in 1956 at the Dartmouth Artificial Intelligence Research Project. 

AI has many well-known components, such as speech recognition, machine learning, and natural language processing. Java, Python, and R are three programming languages that are synonymous with AI technology. 

AI systems in business gather complex data and analyze it for patterns and similarities. It then employs these patterns to forecast the future. 

What is Patent Search and Monitoring? 

A patent search is a one-time process that identifies previously published patent documents that are pertinent to your patent search. If you want to determine whether your own invention is novel enough to guarantee a patent application, look for patents that disclose the same inventive solution. However, if you want to launch a new product and avoid infringing on any patent documents, you are primarily looking for patents that provide specific legal coverage. 

There are following types of patent monitoring: 

1. Technology Watch: This monitoring procedure focuses on locating patent documents for a specific technology in which the searcher is interested. Technology Watch alerts you when a technology pattern matures in the industry. This allows industry stakeholders to identify fresh entrants in their field and differentiate which may pose a significant competition.
2. Competitor Watch: Companies use this monitoring process to focus on the activities of their competitors. They can view their competitors’ most recent patent filings and use the information to alter their business strategies.

What is the significance of patent search and monitoring? 

A patent search is an important first step for a company before venturing into a new field. 

The monitoring results provide the company with regular updates on changes and potential infringement risks in the industry, as well as the latest technological trends. Overall, it assists a company in saving money on avoidable errors. 

Now consider some of the advantages of patent search and monitoring.

1. It assists businesses in forecasting market strategies.

The primary goal of patent search and monitoring is to comprehend the market strategy of the competitor. For example, it assists them in determining what aspects of their product make them leaders in a particular field. 

Understanding this will aid a company’s introspection and strategy revision. Using this knowledge, they can evaluate their structure and build it to a competitive level.

2. Detecting Infringement of Patented Technology

A company can determine whether its product infringes on third-party patents by conducting patent searches or monitoring. This knowledge will protect a company from incurring extraordinary costs to settle an infringement case. 

It also gives them time to change their innovation to something that will not interfere with another patent.

3. Identifying New and Viable Investment Areas

Assume a company conducts a patent search and finds that its innovation is a newcomer to the industry. This implies that the competition has gained enough market share to make it difficult for new entrants to enter the same market. 

In that case, the company can refocus its search on emerging technologies. Patent search and monitoring can assist in identifying these areas that may improve investment results. 

If a company enters a highly competitive industry, it may suffer significant losses.

4. Identifying Expanding Markets in an Industry

The reason for monitoring patent activities could be to track the progress of a competitor. A good business strategy is to research a competitor’s areas of growth and development. 

This can assist a company in developing innovation in a previously unknown area of technology. They can improve existing processes to account for changing market conditions. 

Focusing on a new area benefits startups more than established organizations. It reduces competition and makes it easier to differentiate themselves from new customers rather than attempting to break into competitor-dominated markets. 

Other advantages of patent search and monitoring include: 

• It provides information that is useful for potential mergers and acquisitions. 
• Patent search and monitoring assist businesses in determining when a specific patent application may be opposed. This is useful when they have legitimate grounds to challenge the other company’s patent application. 

How AI Can Facilitate Patent Search and Monitoring 

The number of patents filed each year is increasing, making it difficult for many businesses to keep up. To stay current on their competitors’ patenting activities, a typical technological company must analyze between 100 and 500 documents weekly. 

To identify the relevant patent documents, conventional search methods involve creating a Boolean search. 

However, as the number of patent filings increases, it has become increasingly difficult to examine and evaluate all of the patent documents captured by the patent search or monitoring process in order to determine the most important patents. 

This is where AI technology can help. It can quickly scan through the captured data set of a patent search or monitoring and retrieve and identify the subset of patent documents that are truly relevant. 

AI saves time and money while providing high-quality, accurate data. The AI always performs at its peak; it is unaffected by stress, lack of sleep, or mood swings. Furthermore, AI ensures that the entire patent document is scanned and analyzed before drawing any conclusions and making any rash decisions. 

This provides an advantage to the person conducting the patent search and/or monitoring. Certain AI algorithms can help organize data based on its relevance. 

Conclusion 

With the rapid increase in patent filings, people are looking for the most effective AI solutions capable of quickly identifying patent documents relevant to the designated person and organization from larger data sets. As a result, the intellectual review time can be spent on the relevant patents identified by the AI tool rather than sorting through irrelevant patent documents. AI-based patent search and monitoring tools, such as XLSCOUT’s Novelty Checker, can assist businesses in quickly identifying and gathering useful information that can be used to verify patent activity in a specific sector. 

Our Methodology

The Novelty Checker makes patent searches easier for inventors. The tool searches for similar inventions to yours to determine whether a patent is feasible. 

A step-by-step guide to conducting an AI-based patent search with Novelty Checker can be accessed by clicking here.

XLSCOUT put the use of reinforcement learning to its AI-based Novelty Checker (patent searching tool) to get quality patent research reports in just 5 minutes. The Novelty Checker uses reinforcement learning to filter the noise from the prior art by pulling up the relevant results on top of the list. To be precise, it assists in conducting patentability search to help you ensure that your innovation is unique. By selecting a few relevant and non-relevant results, users can apply them to the result set. The system takes the user’s feedback and then learns from it. It uses conceptual searching and re-ranks the results by bringing the quality results to the top and sending the noise to the bottom.    

Without reinforcement learning, users go through hundreds of results manually. By applying this process, users can skip going through the non-relevant results. Reinforcement can also be applied multiple times to a result set according to users’ different requirements/criteria. Users can then view the Top-10 or Top-20 results for each criterion to perform a prior-art analysis for idea validation. Users can quickly generate an automated novelty report by selecting these Top-10 or 20 results.