Summary of Paths Of a Million People: Extracting Life Trajectories From Wikipedia, by Ying Zhang et al.
Paths of A Million People: Extracting Life Trajectories from Wikipedia
by Ying Zhang, Xiaofeng Li, Zhaoyang Liu, Haipeng Zhang
First submitted to arxiv on: 25 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Information Retrieval (cs.IR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel ensemble model called COSMOS is proposed in this paper to tackle the problem of extracting life trajectories from Wikipedia biography pages. The model combines semi-supervised learning and contrastive learning to achieve an F1 score of 85.95%. A hand-curated dataset, WikiLifeTrajectory, consisting of 8,852 (person, time, location) triplets is also created as ground truth. To demonstrate the validity of the extracted results, an empirical analysis is performed on the trajectories of 8,272 historians. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us understand how notable people interact with others, providing valuable insights for broader research into human dynamics. The authors mine millions of biography pages from Wikipedia and develop a model that can extract life trajectories. They also create a dataset to test their approach and make it publicly available to facilitate further research. |
Keywords
» Artificial intelligence » Ensemble model » F1 score » Semi supervised
