Abstract
In this paper, a dynamic information foraging approach is proposed. Game theory and more precisely normal-form is used in order to represent the addressed problem. We model the issue of Web information foraging as a game played by a set of self-interested agents that aim to reach relevant Web pages in a short time. We consider a pure strategy, a mixed strategy and a fully mixed strategy respectively for three kinds of players. Finally, we present the experimental results we obtained by applying our approach on the Citation Network Dataset. The results confirm the ability of our approach to find relevant information in an effective and efficient way.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Pirolli, P., Fu, W.T.: SNIF-ACT: a model of information foraging on the world wide web. In: 9th International Conference on User Modeling 2003, UM 2003, Johnstown, PA, USA, June 22–26, pp. 45–54 (2003)
Drias, Y., Kechid, S., Pasi, G.: A novel framework for medical web information foraging using hybrid ACO and Tabu Search. J. Med. Syst. 40(1), 5:1–5:18 (2016). Springer
Shoham, Y., Leyton-Brown, K.: Multiagent systems - algorithmic, game-theoretic, and logical foundations. Cambridge University, pp. I–XX, 1–483 (2010). ISBN 978-0-521-89943-7
Liu, J., Zhang, S.W.: Characterizing web usage regularities with information foraging agents. IEEE Trans. Knowl. Data Eng. 40, 7478–7491 (2004)
Ranganathan, P.: From microprocessors to nanostores: rethinking data-centric systems. IEEE Comput. 44, 39–48 (2011)
World Wide Web size: http://www.worldwidewebsize.com
Tang, J., Zhang, J., Yao, L., Li, J., Zhang, L., ArnetMiner, Z.: Extraction and mining of academic social networks. In: KDD 2008, pp. 990–998 (2008)
The ACM Computing Classification System: http://dl.acm.org/ccs/ccs.cfm
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Drias, Y., Kechid, S. (2017). Dynamic Web Information Foraging Using Self-interested Agents. In: Rocha, Á., Correia, A., Adeli, H., Reis, L., Costanzo, S. (eds) Recent Advances in Information Systems and Technologies. WorldCIST 2017. Advances in Intelligent Systems and Computing, vol 569. Springer, Cham. https://doi.org/10.1007/978-3-319-56535-4_41
Download citation
DOI: https://doi.org/10.1007/978-3-319-56535-4_41
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-56534-7
Online ISBN: 978-3-319-56535-4
eBook Packages: EngineeringEngineering (R0)