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oktober 07, 2003
Självorganisation och data mining/data analys, samt stigmergy
Här är två intressanta artiklar som kombinerar självorganisation och data mining. Jag har ännu bara bläddrat igenom dem. Sist finns lite länkar om stigmergi (stigmergy).
Båda artiklarna är skriva av Vitorino Ramos och Ajith Abraham.
Web Usage Mining Using Artificial Ant Colony Clustering and Genetic Programming.
Abstract
The rapid e-commerce growth has made both business community and customers face a new situation. Due to intense competition on one hand and the customer's option to choose from several alternatives business community has realized the necessity of intelligent marketing strategies and relationship management. Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, creating adaptive Web sites, business and support services, personalization, network traffic flow analysis and so on. The study of ant colonies behavior and their self-organizing capabilities is of interest to knowledge retrieval/management and decision support systems sciences, because it provides models of distributed adaptive organization, which are useful to solve difficult optimization, classification, and distributed control problems, among others. In this paper, we propose an ant clustering algorithm to discover Web usage patterns (data clusters) and a linear genetic programming approach to analyze the visitor trends. Empirical results clearly shows that ant colony clustering performs well when compared to a self-organizing map (for clustering Web usage patterns) even though the performance accuracy is not that efficient when comparared to evolutionary-fuzzy clustering (i-miner) approach.
KEYWORDS: Web Usage Mining, Ant Systems, Stigmergy, Data-Mining, Linear Genetic Programming.
Abstract
While being it extremely important, many Exploratory Data Analysis (EDA) systems have the inhability to perform classification and visualization in a continuous basis or to self-organize new data-items into the older ones (evenmore into new labels if necessary), which can be crucial in KDD - Knowledge Discovery, Retrieval and Data Mining Systems (interactive and online forms of Web Applications are just one example). This disadvantge is also present in more recent approaches using Self-Organizing Maps. On the present work, and exploiting past sucesses in recently proposed Stigmergic Ant Systems a robust online classifier is presented, which produces class decisions on a continuous stream data, allowing for continuous mappings. Results show that increasingly better results are achieved, as demonstraded by other authors in different areas.
KEYWORDS: Ant Systems, Stigmergy, Data-Mining, Exploratory Data Analysis, Image Retrieval, Continuous Classification.
En liten aside
Stigmergi är ett intressant begrepp.
På sidan 23 i Self-Organization in Biological Systems (Amazon-länk) står det:
In situations where many individuals contribute to a collective effort, such a colony of termites building a nest, stimuli provided by the emerging structure itself can be a rich source of information for the individual.
...
In other words, information from the local environment and work-in-progress can guide further activity. As a structure such a termite mound develops, the state of the building continually provide new information for the builders.
In the study of social insects, the term stigmergy (...) has been used
to describe such recursive building activity.
Begreppet stigmergy skapades av P-P Grassé. I boken är det dock endast franska artiklar som refereras.
Man kan läsa mer t.ex. på följande sidor:
Stigmergy and the World-Wide Web
www.stigmergicsystems.com
Stigmergy, Self-Organization, and Sorting in Collective Robotics (PDF)
Swarm Intelligence - varför myror är intressanta av Robert Johansson och Mia Living.
Se även Forskning och Framsteg: Temanummer om självorganisation och dess referenser.
Posted by hakank at oktober 7, 2003 11:15 EM Posted to Komplexitet/emergens | Machine learning/data mining