Introducing our latest advancement on the IPlytics Platform: the new Undeclared Patent Approach.
This innovative feature is designed to provide users with a more comprehensive understanding of the patent landscape by identifying patents that are potentially essential to specific technology standards but have not been formally declared.
Our approach utilizes the Classification algorithm, a sophisticated machine learning tool, to pinpoint these undeclared patents. By leveraging true positive examples, such as pooled patents, alongside true negative examples, the algorithm constructs a broad technology landscape. This iterative process involves subject matter experts who confirm the essentiality of patents, refining the algorithm's accuracy over time.
The new Undeclared Patent Approach allows users to explore a more complete patent landscape, including both SEPs and non-SEPs. This empowers users to independently navigate and refine their analyses, using tools like the semantic essentiality score (SES) to filter results. By providing a clearer view of the patent landscape, this feature supports strategic decision-making, licensing negotiations, and competitive analysis.
Experience the enhanced capabilities of the IPlytics Platform with our new Undeclared Patent Approach and gain deeper insights into the ever-evolving world of technology standards and patents.
The undeclared patent landscape is based on the following steps:
1. Define the Scope:
Begin by defining the scope of the technology area you are interested in. This involves identifying relevant keywords, concepts, and any themes that should be excluded. Providing a technology brief and examples of positive and negative data can help refine the search criteria.
2. Initial Classifier Building:
The initial phase involves uploading a pre-populated set of positive training patents and identifying similar patent families to source a negative training set. This helps the algorithm distinguish between closely related technologies.
3. Evaluation and Feedback:
The classifier is evaluated by internal experts to ensure it accurately captures relevant patents. Feedback from SEP holders is also incorporated to assess the quality and recall rates of the identified patents.
4. Refinement:
Based on the feedback, the classifier is refined to improve its precision and ensure it aligns with the defined scope of the project.
5. Search Execution:
Once the classifier is finalized, it is integrated into the IPlytics Platform. Users can then execute searches to identify undeclared patents within the specified technology landscape. The platform allows users to filter results by various criteria, such as the semantic essentiality score (SES), to further refine the search.
IPlytics has developed patent landscapes for undeclared patents for QI, video coding (AVC, HEVC, VVC) and Wifi (Wifi 4, Wifi 5, Wifi 6).