Structural Feature Engineering for Generative Engine Optimization: How Content Structure Shapes Citation Behavior
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. Our approach decomposes content structure into three hierarchical levels: macro-structure (document architecture), meso-structure (informatio...
| Authors | Junwei Yu, Mufeng Yang, Yepeng Ding et al. |
|---|---|
| Primary category | cs.CL |
| Published | 31 March 2026 |
| Last updated at source | 31 March 2026 |
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