Life Trajectory Classification Research
Fine-grained classification of life trajectories from Wikipedia using LLM and syntactic graph fusion.
Life Trajectory Classification Research
Research on fine-grained classification of life trajectories from Wikipedia using large language models and syntactic graph fusion. Conducted at ShanghaiTech University, Financial Intelligence Laboratory (PI: Haipeng Zhang).
Publication update: Accepted as an oral presentation to the International Conference on Social Computing (ICSC 2026). arXiv
Overview
This project studies how to model biographical trajectories from large-scale Wikipedia-style data. The core idea is to combine textual representations from LLMs with syntactic and graph-based structural signals, so that the model can better capture career paths, role transitions, and fine-grained life-stage patterns.
My Role
- Worked on life trajectory classification from Wikipedia-style biographies.
- Explored the use of LLM features and syntactic graph fusion for richer person-level representations.
- Connected the project to broader interests in real-world data understanding and data-agent research.
Keywords: Life trajectory, Wikipedia, LLM, syntactic graph fusion, graph neural networks, social computing.