MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641078218 A) filed by Cmr Engineering College, Kandlakoyav, Medchal Road, Hyderabad, Medchal Malkajgiri, Telangana-, India. on June 24, 2026, for Artificial Intelligence-Based Multilingual Virtual Research Assistant For Academic Document Analysis.
Inventors include Dr. B. Papachary, Associate Professor, Electronics And Communication Engineering, Cmr Engineering College; Mrs. B. Mamatha, Assistant Professor, Computer Science And Engineering, Cmr Engineering College, Kandlakoya, Hydeabad-; Mr. V Kirankumar, Assistant Professor, Computer Science And; Mrs. A Shravani, Assistant Professor, Computer Science And; Mrs. Anusha Ayyapan, Assistant Professor, Computer Science; Mrs. T. Swathi, Assistant Professor, Computer Science And; and Mr. Lal Bahadur Pandey, Assistant Professor, Computer Science And Engineering Aiml, Cmr Engineering College, Kandlakoya, Hydeabad-.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The present invention discloses an Artificial Intelligence-Based Multilingual Virtual Research Assistant for Academic Document Analysis designed to automate research assistance and document understanding in multilingual academic environments. The system integrates artificial intelligence, natural language processing, and machine learning techniques to analyze academic documents and provide intelligent support for researchers, students, and educators. Academic documents collected from digital libraries, journals, research databases, and user uploads undergo preprocessing operations including text extraction, tokenization, stop word removal, stemming, lemmatization, and language detection. Advanced NLP models perform semantic analysis, named entity recognition, topic modeling, and contextual understanding to extract meaningful information from documents. The framework supports multilingual translation and cross-language analysis, enabling users to access research content in multiple languages. The system further provides automated document summarization, citation extraction, keyword identification, literature review assistance, plagiarism detection, and question answering functionalities. A recommendation engine suggests relevant research papers, journals, and emerging research trends based on user interests and document content. Interactive dashboards and chat-based interfaces facilitate efficient interaction with academic resources. The framework supports cloud-based deployment for scalable implementation across universities, research institutions, digital libraries, and online learning platforms. The proposed invention enhances research productivity, improves accessibility to scholarly information, promotes multilingual collaboration, and enables intelligent knowledge discovery in academic and scientific research environments.
Disclaimer: Curated by HT Syndication.
