MUMBAI, India, Jan. 2 -- Intellectual Property India has published a patent application (202541122641 A) filed by Malla Reddy (MR) Deemed to be University; Malla Reddy University; Malla Reddy Engineering College For Women; Malla Reddy College Of Engineering And Technology; and Malla Reddy Vishwavidyapeeth, Medchal-Malkajgiri, Telangana, on Dec. 5, 2025, for 'dynamic ontology builder for contextual data classification.'
Inventor(s) include Dr. U. Mohan Srinivas; Dr. K. Asish Vardhan; Somasekhar Sanjeevini; Dr. K. Rajeshwar Reddy; and Mrs. Anupama Manepally.
The application for the patent was published on Jan. 2, under issue no. 01/2026.
According to the abstract released by the Intellectual Property India: "The contextual data is classified by using adaptive semantic modeling and machine learning on a dynamic ontology building to ensure automation of these procedures. The scheme produces ontological systems that develop as new data enters into it and thus enables a precise classification and relationship drawing of the various information domains. The system is able to convert any unstructured and semi-structured data into structured, analyzable knowledge representations by using natural language processing, a knowledge graph generation system, and context-based reasoning. The architecture also has an integrated hybrid learning engine that identifies semantic entities, finds relationships, and forms hierarchical taxonomies with their own dynamically. The constant feedback process refines the ontology nodes and relationships as new information is being fed in, making sure that the model keeps up to the changing terminologies in addition to the context developments. The reasoning layer provides inference-based classification to resolve ambiguity and enhance the semantic match between instances of data. The domain experts define constraints, semantic rules, and contextual weights that can be used to guide the ontology development via the use of a user-configurable control module. The framework facilitates interoperability with external data sources, APIs and knowledge repositories and is a scalable solution to enterprise and academic applications. Determination of real-time classification outcomes and graphical representations of visual displays increase interpretability and decision-making. With the integration of automation and semantic reasoning, which is adaptive, the system is revolutionizing the management of static ontology dynamic into an intelligent self-evolving knowledge organization process."
Disclaimer: Curated by HT Syndication.
