Extracting Navigation Hierarchies from Networks with Genetic Algorithms

Stefan John, Michael Granitzer, Denis Helic

Abstract

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.

References

  1. Adamic, L. and Adar, E. (2005). How to search a social network. Social Networks, 27(3):187-203.
  2. Ahmed, N., Neville, J., and Kompella, R. R. (2011). Network sampling via edge-based node selection with graph induction. Technical report, Purdue University.
  3. Brandes, U. (2008). On variants of shortest-path betweenness centrality and their generic computation. Social Networks, 30(2):136-145.
  4. Carvalho, P. M. S., Ferreira, L. A. F. M., and Barruncho, L. M. F. (2001). On spanning-tree recombination in evolutionary large-scale network problems-application to electrical distribution planning. Evolutionary Computation, IEEE Transactions on, 5(6):623-630.
  5. Clauset, A., Moore, C., and Newman, M. E. (2008). Hierarchical structure and the prediction of missing links in networks. Nature, 453(7191):98-101.
  6. Field, A., Miles, J., and Field, Z. (2014). Discovering statistics using R. SAGE Publications.
  7. Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley Professional.
  8. Haupt, R. L. (2000). Optimum population size and mutation rate for a simple real genetic algorithm that optimizes array factors. In Antennas and Propagation Society International Symposium, 2000. IEEE, volume 2, pages 1034-1037. IEEE.
  9. Helic, D., Strohmaier, M., Granitzer, M., and Scherer, R. (2013). Models of human navigation in information networks based on decentralized search. In Proceedings of the 24th ACM Conference on Hypertext and Social Media, pages 89-98. ACM.
  10. Heymann, P. and Garcia-Molina, H. (2006). Collaborative creation of communal hierarchical taxonomies in social tagging systems. Technical report, Stanford InfoLab.
  11. Kleinberg, J. (2000a). Navigation in a small world. Nature, 406(6798):845-845.
  12. Kleinberg, J. (2000b). The small-world phenomenon: An algorithmic perspective. In Proceedings of the thirtysecond annual ACM symposium on Theory of computing, pages 163-170. ACM.
  13. Kleinberg, J. (2002). Small-world phenomena and the dynamics of information. Advances in neural information processing systems, 1:431-438.
  14. Krishnamurthy, V., Faloutsos, M., Chrobak, M., Lao, L., Cui, J.-H., and Percus, A. G. (2005). Reducing large internet topologies for faster simulations. In NETWORKING 2005. Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems, pages 328-341. Springer.
  15. Leskovec, J. and Faloutsos, C. (2006). Sampling from large graphs. In Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 631-636. ACM.
  16. Lovász, L. (1993). Random walks on graphs: A survey. Combinatorics, Paul erdos is eighty, 2(1):1-46.
  17. McAuley, J. J. and Leskovec, J. (2012). Learning to discover social circles in ego networks. In NIPS, volume 272, pages 548-556.
  18. Milgram, S. (1967). The small world problem. Psychology today, 2(1):60-67.
  19. Muchnik, L., Itzhack, R., Solomon, S., and Louzoun, Y. (2007). Self-emergence of knowledge trees: Extraction of the wikipedia hierarchies. Physical Review E, 76(1):016106.
  20. Strohmaier, M., Helic, D., Benz, D., Körner, C., and Kern, R. (2012). Evaluation of folksonomy induction algorithms. ACM Trans. Intell. Syst. Technol., 3(4):74:1- 74:22.
  21. Trattner, C., Singer, P., Helic, D., and Strohmaier, M. (2012). Exploring the differences and similarities between hierarchical decentralized search and human navigation in information networks. In Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies, page 14. ACM.
  22. Wasserman, S. (1994). Social network analysis: Methods and applications, volume 8. Cambridge university press.
  23. West, R. and Leskovec, J. (2012). Human wayfinding in information networks. In Proceedings of the 21st international conference on World Wide Web, pages 619- 628. ACM.
  24. West, R., Pineau, J., and Precup, D. (2009). Wikispeedia: An online game for inferring semantic distances between concepts. In IJCAI, pages 1598-1603.
Download


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

@conference{webist16,
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,},
year={2016},
pages={63-74},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005760600630074},
isbn={978-989-758-186-1},
}


in EndNote Style

TY - CONF
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