Exploring human behavior: Modeling human navigation of information networks
We are confronted with massive amounts of in- formation at every turn. In order to efficiently reason about knowledge and information, humans have evolved efficient strategies for organizing complex concepts in order to form connections between and recall information. This behavior can be observed and codified when people search for objects within digital information networks. Current models of search behavior exhibit unnecessary or extraneous complexity. Minimal or simple modifications to well established algorithms yield valid models of human navigation by exploring hierarchical information inherent in networks. We explore and validate a new model of how humans navigate an information networks. To that end, we present a new path finding algorithm that approximates human navigation by leveraging the categorical classification of the nodes within the network. We compare our new model, CatPath, to existing graph distance measures when possible and show that the category paths are largely correlated with traces of human navigation.
- Venue: 2015 IEEE International Conference on Big Data (Big Data)
- Title: Concept Hierarchies and Human Navigation
- Authors: Salvador Aguinaga∗, Aditya Nambiar†, Zuozhu Liu‡ and Tim Weninger∗ ∗University of Notre Dame, Email: {saguinag, tweninge}@nd.edu, †IIT Bombay, Email: [email protected], ‡Zhejiang University, Email: [email protected]