AI turns semantic relationships into geometric relationships
- for: key idea, key idea - language research , AI - language research - semantic to geometric
AI turns semantic relationships into geometric relationships
here's a trivial example of why the "standard" geometric mean is not a good estimate of central tendency when you have values near zero.
Data that combine multiplicatively, like rates, are actually very common outside of economics too. The key is to recognize when a measured variables is affected by many (semi) independent forces, each of which scales that variable up or down — rather than simply adding or subtracting a fixed amount to it. This is often true in the natural sciences.
Ortiz, E., & Serrano, M. Á. (2021). Multiscale opinion dynamics on real networks. ArXiv:2107.06656 [Physics]. http://arxiv.org/abs/2107.06656
Ortiz, E., García-Pérez, G., & Serrano, M. Á. (2020). Geometric detection of hierarchical backbones in real networks. ArXiv:2006.03207 [Physics]. http://arxiv.org/abs/2006.03207
Distance from a point to a line segment
Lines and Distance of point to line
point: P
line_seg_start_point: P0
line_seg_end_point: P1