AI RESEARCH
Structural Feature Engineering for Generative Engine Optimization: How Content Structure Shapes Citation Behavior
arXiv CS.CL
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ArXi:2603.29979v1 Announce Type: new The proliferation of AI-powered search engines has shifted information discovery from traditional link-based retrieval to direct answer generation with selective source citation, creating new challenges for content visibility. While existing Generative Engine Optimization (GEO) approaches focus primarily on semantic content modification, the role of structural features in influencing citation behavior remains underexplored. In this paper, we propose GEO-SFE, a systematic framework for structural feature engineering in generative engine optimization.