Extracting Navigation Hierarchies from Networks with Genetic Algorithms

Stefan John, Michael Granitzer, Denis Helic


Information networks are nowadays an important source of knowledge, indispensable for our daily tasks. Because of their size, however, efficient navigation can be a challenge. Following the idea to use network hierarchies as guidance in human as well as algorithmic search processes, this work focuses on the creation of optimized navigation hierarchies. Based on an established model of human navigation, decentralized search, we defined two quality criteria for network hierarchies and propose a genetic algorithm applying them. We conducted experiments on an information as well as a social network and analyzed the optimization effectivity of our approach. Furthermore, we investigated the structure of the resulting navigation hierarchies. We found our algorithm to be well-suited for the task of hierarchy optimization and found distinct structural properties influencing the quality of navigational hierarchies.


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Paper Citation

in Harvard Style

John S., Granitzer M. and Helic D. (2016). Extracting Navigation Hierarchies from Networks with Genetic Algorithms . In Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST, ISBN 978-989-758-186-1, pages 63-74. DOI: 10.5220/0005760600630074

in Bibtex Style

author={Stefan John and Michael Granitzer and Denis Helic},
title={Extracting Navigation Hierarchies from Networks with Genetic Algorithms},
booktitle={Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,},

in EndNote Style

JO - Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,
TI - Extracting Navigation Hierarchies from Networks with Genetic Algorithms
SN - 978-989-758-186-1
AU - John S.
AU - Granitzer M.
AU - Helic D.
PY - 2016
SP - 63
EP - 74
DO - 10.5220/0005760600630074