#3770 Patent Opportunities

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#3770 Patent Opportunities

AI-based patent abstract generator can discover and detail technology opportunities

https://techxplore.com/news/2025-10-ai-based-patent-abstract-generator.html

#3770 Familiarize yourself with https://techxplore.com/news/2025-10-ai-based-patent-abstract-generator.html



Describe this system applied to a knowledge graph

Of course. Applying the AI-based patent abstract generator to a knowledge graph would transform it from a static map of existing technologies into a dynamic tool for predicting and describing future innovations.

Instead of just identifying empty spaces on a 2D map, the system would analyze the structure and relationships within the knowledge graph to pinpoint and articulate potential technological breakthroughs.

Representing Technology as a Knowledge Graph

First, the entire patent landscape would be modeled as a knowledge graph. In this graph:

  • Nodes would represent key entities such as individual patents, specific technologies (e.g., LiDAR, neural networks), inventors, companies, and scientific concepts.

  • Edges would represent the relationships between these nodes. For example, an edge could connect two patents if one cites the other, link an inventor to their patents, or connect a technology to the patents that utilize it.

This creates a rich, multi-dimensional network of interconnected information, far more detailed than a simple 2D patent map.

Identifying "Knowledge Vacancies"

The core function of the AI system is to find "vacancies." In the context of a knowledge graph, a vacancy wouldn't be an empty physical space, but rather a missing or weak connection between related nodes. The system would analyze the graph to find areas that are logically adjacent but have few or no direct links.

For instance, the graph might show strong clusters of nodes for "wearable health sensors" and "real-time glucose monitoring." It might also have a strong cluster for "microneedle technology." However, the system might detect a very weak or non-existent direct link between "microneedle arrays" and "wearable, real-time glucose sensors." This structural gap represents a "knowledge vacancy"—a potential area for a new invention.

Generating the Missing Link 💡

This is where the AI-based abstract generator would be applied.

  1. Analyze the Gap: The system would analyze the attributes of the nodes surrounding the identified vacancy (in our example, the concepts of microneedles and wearable glucose sensors).

  2. Generate a "Ghost Node": Using its text embedding inversion technique, the AI would translate this structural gap into human-readable text. It would generate a detailed patent abstract for a hypothetical invention that would bridge this gap.

  3. Articulate the Opportunity: The generated abstract would effectively describe the "missing link." For example, it might generate an abstract titled: "A Wearable Patch with Biodegradable Microneedles for Continuous, Minimally Invasive Glucose Monitoring." This abstract would become a concrete description of the innovation needed to fill that technological gap.

By applying this system to a knowledge graph, researchers and strategists could move beyond simply seeing that a gap exists. They could instantly read a detailed description of the specific technology that could fill that gap, thereby accelerating R&D, guiding investment, and systematically exploring the frontiers of innovation.


From <https://gemini.google.com/app>  Google Gemini 2.5 Pro

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