EIN-WUM: an AIS-based algorithm for web usage mining

Authors:
Adel Torkaman Rahmani;B. Hoda Helmi
Affiliations:
Iran University of Science and Technology, Tehran, Iran;Iran University of Science and Technology, Tehran, Iran
Venue:
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Year:
2008

Citing 2
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Artificial Immune Systems: A New Computational Intelligence Paradigm

Artificial Immune Systems: A New Computational Intelligence Paradigm
A framework for mining evolving trends in web data streams using dynamic learning and retrospective validation

Computer Networks: The International Journal of Computer and Telecommunications Networking - Web dynamics

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Abstract

With the ever expanding Web and the information published on it, effective tools for managing such data and presenting information to users based on their needs are becoming necessary. In this paper, we propose a new algorithm named "EIN-WUM" for Web usage mining based on artificial immune system metaphor. This algorithm introduces several novelties such as using danger theory, directed mutation and an enhanced immune network model. Experimental results show that The EIN-WUM algorithm can properly learn the frequent trends in noisy, sparse and huge Web usage data in single pass.