Heidelberg, Germany

Gorjan Radevski

This inventor holds 1 USPTO granted patent. Top assignee: Nec Corporation. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Gorjan Radevski. Retrieved from https://idiyas.com/inventor/gorjan-radevski

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank

Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

Loading Chart...
1 patent (USPTO):Explore Patents

Title: Gorjan Radevski: Inventor Advancing Knowledge-Graph Disambiguation.

Introduction

Gorjan Radevski is an inventor based in Heidelberg, Germany, whose work addresses how information extracted from text can be organized and clarified using knowledge graphs. He works at NEC Corporation and is named on one patent.

Latest Patents

Radevski’s patent, “Grouping and Linking Facts from Text to Remove Ambiguity Using Knowledge Graphs,” describes a method for disambiguating facts extracted from textual data. The method represents each fact as a subject–relation–object triple, ranks the facts, and determines whether each element should link to an existing entry in a reference knowledge graph or be added as a new entry. The resulting enriched knowledge graph can support decision-making across applications such as drug development, material synthesis, inventory management, suspect detection from textual messages, and healthcare. The patent also describes using a machine-learning ranking module. Radevski has 1 patent.

Career Highlights

At NEC Corporation, Radevski’s patented work focuses on connecting textual information with structured knowledge. By resolving ambiguity in extracted facts, the approach aims to make information more useful for analysis and decision-making.

Collaborations

Radevski’s named coworkers include Kiril Gashteovski and Carolin Lawrence.

Conclusion

Gorjan Radevski’s patent presents a knowledge-graph approach to clarifying facts from text, with potential applications spanning healthcare, research, and other information-intensive fields.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
Loading…