Xionghui Wen
Papers
2
Total Citations
9
H-Index
2
About
Xionghui Wen is a researcher at the forefront of technology foresight and patent-driven innovation, with a specialized focus on industrial and service robotics. His work uniquely bridges the gap between big data analytics and mechanical engineering, primarily through the mining of patent landscapes to predict technological trajectories. Wen’s most impactful contribution, the 2019 paper "Technology Foresight Research of Industrial Robot Based on Patent Analysis" (6 citations), introduces an improved methodology that leverages SAO (Subject-Action-Object) structure extraction from patent big data to calculate inter-patent similarity, offering a systematic approach to forecasting industrial robot trends. Complementing this, his 2017 study on "A Method for Patent Mining and Its Application in Innovation of High-Altitude Cleaning Robot" (3 citations) applies these techniques to address real-world challenges in the burgeoning high-rise cleaning industry, identifying technological gaps and proposing novel solutions. Though his citation counts are modest, Wen’s work is notable for pioneering the integration of knowledge maps with patent mining, providing a replicable framework for researchers and engineers aiming to drive innovation through data-driven foresight. His research is particularly valuable for students and professionals seeking to understand how patent analytics can inform strategic R&D in robotics.
Research Focus
Key Achievements
Top Papers
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