The exploration of relevant prior art is an important part of the innovation lifecycle. From competitive intelligence to resource allocation, thorough prior art analysis guides your company’s IP strategy. Understanding what inventions have already been documented enables you to concentrate your research and development efforts on truly novel and non-obvious inventions. Prior art analysis may even spark an even more inventive idea than the one you were working on before!
What is Prior Art?
Prior art includes all publicly disclosed inventions prior to yours. The most obvious place to look for ideas is in patent documentation, which includes pending, rejected, and abandoned patents. A thorough examination of relevant prior art, on the other hand, includes non-patent literature as well. Defensive publications, scientific and academic papers and presentations, technical standards, and other similar documents frequently contain critical information.
Why Examine Prior Art?
The first step is to locate patent and non-patent literature pertinent to your new concept. In order to make well-informed decisions about your R&D and any resulting IP, your organization must be able to extract insights from these documents. This allows you to reduce risks while increasing opportunities. Prior art, when used correctly, can provide insights into:
- Competitive Intelligence: Discover where your competitors are innovating—and where they aren’t.
- Market Positioning: It entails finding new ways to solve your customers’ problems.
- Research Direction: Focus research resources on white space in the technology landscape.
- Investment Prospecting: Identify new technologies, markets, and M&A targets for allocating IP budgets.
Above all, thorough prior art analysis increases the likelihood that your innovation is novel and non-obvious, and thus patentable.
Conducting a Thorough Prior Art Analysis
Finding highly relevant documents among the massive amount of patent and non-patent literature and trying to extract valuable insights from them is the challenge of thorough prior art analysis. XLSCOUT‘s Novelty Checker uses semantic search to help stakeholders throughout the innovation lifecycle find what they’re looking for.
Inventors, engineers, and scientists, as well as IP professionals, can use a combination of natural language search queries and relevant filters to search millions of documents. The artificial intelligence-powered search engine returns results from major patent-issuing authorities in the United States, China, Europe, South Korea, Germany, and Australia, as well as the World Intellectual Property Organization and others. Your search results will also contain relevant non-patent prior art from the prior art databases of IEEE and XLSCOUT.
Our Methodology
XLSCOUT put the use of reinforcement learning to its AI-based Novelty Checker patent search tool to get quality patent research reports in just 5-7 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/patent research 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 and patentability search report by selecting these Top-10 or 20 results. The Novelty Checker prior art search reports include a list of results along with relevant text mapping with the key features of the invention for enabling quick decision-making.
