In this work, we conceptualize career histories as traversals through a temporal multi-modal network describing individuals\' different positions at various organizations across time. We describe methods for clustering and visualizing career histories using a multi-relational, multi-dimensional approach. We show how we can discover patterns in career trajectories, using a variety of structural similarity measures and identify common motifs and detect anomalies. We show results on a dataset describing the recent career histories of US NCAA basketball coaches.

@InProceedings{sharara:sunbelt11,
  author       = "Sharara, Hossam and Halgin, Daniel and Getoor, Lise and Borgatti, Steve",
  title        = "Multi-dimensional Trajectory Analysis for Career Histories",
  booktitle    = "International Sunbelt Social Networks Conference (Sunbelt XXXI)",
  year         = "2011",
}