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- <strong>UNITED STATES PATENT APPLICATION</strong><br><br>
- <strong>Patent No.:</strong> US 2025/0001234 A1<br>
- <strong>Date of Publication:</strong> January 3, 2025<br>
- <strong>Filed:</strong> July 5, 2025<br><br>
- <strong>Title:</strong><br>
- Patent Plus AI: Intelligent Patent Summarization and Trend Prediction System<br><br>
- <strong>Inventors:</strong> Tran, Tien (Ho Chi Minh City, Vietnam)<br>
- <strong>Assignee:</strong> Patent Plus Technologies Inc.<br><br>
- <strong>Abstract:</strong><br>
- A system and method for AI-driven summarization and trend analysis of patent documents. The system ingests large
- datasets of patents, extracts core claims, summarizes prior art, and predicts emerging innovation trends using
- machine learning techniques. Designed to aid legal professionals, inventors, and researchers in efficiently
- navigating patent landscapes.<br><br>
- <strong>Claims:</strong><br>
- 1. A method for processing patent documents comprising:<br>
- a) extracting metadata including title, abstract, inventor, and assignee;<br>
- b) using natural language processing to summarize the abstract and claims;<br>
- c) applying a transformer-based AI model to cluster similar inventions by topic and field;<br>
- d) generating a predictive score indicating future patent activity in a specific domain.<br><br>
- 2. The method of claim 1, further comprising a web-based user interface that highlights key patent terms,
- visualizes citation networks, and allows users to search and filter by AI-generated tags.<br><br>
- 3. The method of claim 1, wherein the predictive score is derived using a time series model trained on USPTO
- patent filing trends, inventor recurrence, and claim complexity.<br><br>
- <strong>Description:</strong><br><br>
- <strong>Field of the Invention:</strong><br>
- The present invention relates generally to the field of artificial intelligence and patent law, and more
- specifically to systems that analyze, summarize, and forecast innovation trends based on patent filings.<br><br>
- <strong>Background:</strong><br>
- With millions of patents published globally each year, it has become increasingly difficult for professionals to
- track and understand innovation developments. Existing solutions lack intelligent summarization and
- forward-looking analytics.<br><br>
- <strong>Summary:</strong><br>
- Patent Plus AI offers a solution by combining transformer-based natural language processing, citation graph
- analysis, and trend forecasting models. The system processes bulk patent data and provides streamlined summaries
- and predictions.<br><br>
- <strong>Detailed Description:</strong><br>
- An AI pipeline begins with a document ingestion module that parses .pdf or .xml patent files. A preprocessing
- module extracts structured and unstructured text fields. The summarization engine is built upon a fine-tuned
- BERT variant, while the trend prediction module utilizes Prophet (time-series forecasting) and XGBoost
- classifiers trained on historical patent metrics.<br><br>
- The final outputs are rendered in a dashboard view, accessible via browser or API, allowing stakeholders to make
- data-driven IP strategy decisions.<br><br>
- <strong>Drawings:</strong><br>
- Fig. 1 – System Architecture of Patent Plus AI<br>
- Fig. 2 – Example of Citation Graph Clustering<br>
- Fig. 3 – Trend Prediction Output for AI Patents (2015–2025)<br><br>
- <strong>References Cited:</strong><br>
- • US20190345678A1<br>
- • WO2021145678A1<br>
- • "DeepPatent: Patent Classification with BERT", IEEE, 2022<br><br>
- Let me know if you want a PDF version, or to customize the invention (e.g., AI for medicine, green tech, etc.).
- </p>
- </div>
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