Yung‐Chang Hsiao

Papers

Total Citations

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About

Yung‐Chang Hsiao’s research centers on the intersection of artificial intelligence, patent informatics, and ontology engineering, with a focus on developing intelligent systems for technology evaluation and recommendation. His most-cited work, "Ontology-based GFML agent for patent technology requirement evaluation and recommendation" (2017, 11 citations), introduces a novel framework that leverages ontology and fuzzy markup language to automate the analysis of patent requirements, enabling more efficient technology matching and decision support. This contribution is particularly impactful for intellectual property management and innovation analytics, offering a structured approach to handling complex, unstructured patent data. Hsiao’s work bridges the gap between semantic technologies and practical patent analysis, demonstrating how AI agents can enhance the accuracy and speed of technology requirement assessments. His research is notable for its applied focus, providing tools that assist researchers, patent analysts, and R&D teams in navigating the vast landscape of patented technologies. With a growing citation footprint, Hsiao’s contributions continue to influence the fields of knowledge engineering and patent analytics, positioning him as a key figure in the development of ontology-driven solutions for intellectual property challenges.