Figure – Web Usage Mining of Monash’s Univ. web site using self-organized ant-based clustering (initial and final classification maps). Web usage Data was collected from the Monash University’s Web site (Australia), with over 7 million hits every week.
[] Vitorino Ramos, Ajith Abraham, Evolving a Stigmergic Self-Organized Data-Mining, in ISDA-04, 4th Int. Conf. on Intelligent Systems, Design and Applications, Budapest, Hungary, ISBN 963-7154-30-2, pp. 725-730, August 26-28, 2004.
Self-organizing complex systems typically are comprised of a large number of frequently similar components or events. Through their process, a pattern at the global-level of a system emerges solely from numerous interactions among the lower-level components of the system. Moreover, the rules specifying interactions among the system’s components are executed using only local information, without reference to the global pattern, which, as in many real-world problems is not easily accessible or possible to be found. Stigmergy, a kind of indirect communication and learning by the environment found in social insects is a well know example of self-organization, providing not only vital clues in order to understand how the components can interact to produce a complex pattern, as can pinpoint simple biological non-linear rules and methods to achieve improved artificial intelligent adaptive categorization systems, critical for Data-Mining. On the present work it is our intention to show that a new type of Data-Mining can be designed based on Stigmergic paradigms, taking profit of several natural features of this phenomenon. By hybridizing bio-inspired Swarm Intelligence with Evolutionary Computation we seek for an entire distributed, adaptive, collective and cooperative self-organized Data-Mining. As a real-world / real-time test bed for our proposal, World-Wide-Web Mining will be used. Having that purpose in mind, Web usage Data was collected from the Monash University’s Web site (Australia), with over 7 million hits every week. Results are compared to other recent systems, showing that the system presented is by far promising.
(to obtain the respective PDF file follow link above or visit chemoton.org)
3 comments
Comments feed for this article
9 April, 2010 at 9:00 am
Christophe Guéret
Interesting post !
I would like to indicate that for people interested in the application of self-organisation in Complex Systems we are organising in Amsterdam a symposium on Self-organisation in Knowledge Systems: http://www.few.vu.nl/soks/symposium
On two days, we will discuss how self-organisation princicple and, on a broader perspective, computational intelligence techniques can be used to deal with the messiness of the Web of Data.
9 April, 2010 at 12:14 pm
Tweets that mention Evolving a Stigmergic Self-Organized Data Mining « Chemoton § Vitorino Ramos' research notebook -- Topsy.com
[…] This post was mentioned on Twitter by Ali Sohani, stefano bertolo, John Idol, topsy_top20k, topsy_top20k_en and others. topsy_top20k_en said: Over 7 million web site hits every week analysed by Ant Colonies #Web #Data #Mining http://bit.ly/9WLP7A […]
10 April, 2010 at 3:31 pm
Vitorino Ramos
Thanks Christophe. I did received your symposium CFP as well via email. I will tweeted around as well. Cheers, v.