· 3 months ago · Jul 09, 2025, 03:05 PM
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355 <strong>UNITED STATES PATENT APPLICATION</strong><br><br>
356
357 <strong>Patent No.:</strong> US 2025/0001234 A1<br>
358 <strong>Date of Publication:</strong> January 3, 2025<br>
359 <strong>Filed:</strong> July 5, 2025<br><br>
360
361 <strong>Title:</strong><br>
362 Patent Plus AI: Intelligent Patent Summarization and Trend Prediction System<br><br>
363
364 <strong>Inventors:</strong> Tran, Tien (Ho Chi Minh City, Vietnam)<br>
365 <strong>Assignee:</strong> Patent Plus Technologies Inc.<br><br>
366
367 <strong>Abstract:</strong><br>
368 A system and method for AI-driven summarization and trend analysis of patent documents. The system ingests large
369 datasets of patents, extracts core claims, summarizes prior art, and predicts emerging innovation trends using
370 machine learning techniques. Designed to aid legal professionals, inventors, and researchers in efficiently
371 navigating patent landscapes.<br><br>
372
373 <strong>Claims:</strong><br>
374 1. A method for processing patent documents comprising:<br>
375 a) extracting metadata including title, abstract, inventor, and assignee;<br>
376 b) using natural language processing to summarize the abstract and claims;<br>
377 c) applying a transformer-based AI model to cluster similar inventions by topic and field;<br>
378 d) generating a predictive score indicating future patent activity in a specific domain.<br><br>
379
380 2. The method of claim 1, further comprising a web-based user interface that highlights key patent terms,
381 visualizes citation networks, and allows users to search and filter by AI-generated tags.<br><br>
382
383 3. The method of claim 1, wherein the predictive score is derived using a time series model trained on USPTO
384 patent filing trends, inventor recurrence, and claim complexity.<br><br>
385
386 <strong>Description:</strong><br><br>
387
388 <strong>Field of the Invention:</strong><br>
389 The present invention relates generally to the field of artificial intelligence and patent law, and more
390 specifically to systems that analyze, summarize, and forecast innovation trends based on patent filings.<br><br>
391
392 <strong>Background:</strong><br>
393 With millions of patents published globally each year, it has become increasingly difficult for professionals to
394 track and understand innovation developments. Existing solutions lack intelligent summarization and
395 forward-looking analytics.<br><br>
396
397 <strong>Summary:</strong><br>
398 Patent Plus AI offers a solution by combining transformer-based natural language processing, citation graph
399 analysis, and trend forecasting models. The system processes bulk patent data and provides streamlined summaries
400 and predictions.<br><br>
401
402 <strong>Detailed Description:</strong><br>
403 An AI pipeline begins with a document ingestion module that parses .pdf or .xml patent files. A preprocessing
404 module extracts structured and unstructured text fields. The summarization engine is built upon a fine-tuned
405 BERT variant, while the trend prediction module utilizes Prophet (time-series forecasting) and XGBoost
406 classifiers trained on historical patent metrics.<br><br>
407
408 The final outputs are rendered in a dashboard view, accessible via browser or API, allowing stakeholders to make
409 data-driven IP strategy decisions.<br><br>
410
411 <strong>Drawings:</strong><br>
412 Fig. 1 – System Architecture of Patent Plus AI<br>
413 Fig. 2 – Example of Citation Graph Clustering<br>
414 Fig. 3 – Trend Prediction Output for AI Patents (2015–2025)<br><br>
415
416 <strong>References Cited:</strong><br>
417 • US20190345678A1<br>
418 • WO2021145678A1<br>
419 • "DeepPatent: Patent Classification with BERT", IEEE, 2022<br><br>
420
421 Let me know if you want a PDF version, or to customize the invention (e.g., AI for medicine, green tech, etc.).
422 </p>
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