The network properties of episodic graphs. Zhuang, Sreekumar, Belkin, Dennis. 2012? Poster?


  1. “We present statistical analyses of the small world properties for two particular types of episodic graphs. One is from the paragraph space of the Internet Movie Database (IMDb) and the other is from images collected as subjects engaged in their activities of daily living. We show that they have a small-world structure which is characterized by sparse connectivity, short average path lengths between nodes, and high global clustering coefficient. However, the degree distribution analyses show that they are not scale-free graphs.”
  2. Deals with models for episodic memory – how are context cues used?
  3. One idea is memory forms a network and cues help search
  4. As an approximation, they analyze graph structure of gossip stories on IMDB as well as SenseCam activity logging cameras
  5. Seems like they use very simple bag of words and color histogram to measure closeness <I should look at this more carefully later>
    1. <Not clear on how they then picked neighbors but may be stocastic transitions with weights equal to similarities>
    2. <If I understand this methodology, I don’t think its what I would use>
  6. Heavily pruned edges, at leas the IMDB dataset looks pretty similar to a random graph if pruning is not done
  7. High global clustering and short path lengths
    1. Small world structure, but no scale free property
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