MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202541029899 A) filed by Samyuktha R P; Arunadevi K; Darshna S; Harini S; and Ammu V on March 28, 2025, for Pesonalized Multi-Document Text Summarization Using Deep Learning Techniques.
Inventors include Samyuktha R P; Arunadevi K; Darshna S; Harini S; and Ammu V.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: ABSTRACT OF THE INVENTION: The invention introduces an AI-powered multi-document text summarization system that leverages deep ·learning techniques to generate concise, coherent, and personalized summaries from multiple input documents. Traditional summarization methods often lack contextual understanding and adaptability to user preferences. To address these limitations, this invention utilizes transformer-based models such as GPT-4o, enabling the system to extract key information while preserving meaning, coherence, and readability. A key innovation of this system IS its personalization feature, allowing users to define preferences such as summary length, focus areas, keywords, and summarization type (abstractive/extractive). The system also incorporates reinforcement learning, continuously improving summary quality based on user feedback. The implementation consists of a Flask-based backend API, which processes user inputs and interacts with the deep learning model. A web-based interface (HTML, CSS, JSON) enables users to upload multiple documents (PDF, DOCX, TXT), customize summarization parameters, and receive instant results. This invention has applications across various industries, including academic research, journalism, healthcare, legal documentation, and business analytics, where handling and summarizing large volumes of text is crucial. By automating and personalizing the summarization process, the system significantly enhances efficiency, reduces information overload, and improves decision-making.
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