Swarms on Continuous Data

Details Swarms on Continuous Data Swarms on Continuous Data

2004-12-17

arxiv.org/abs/cs/0412072v1

CEC 03 - Congress on Evolutionary Computation, IEEE Press, ISBN 0780378040, pp.1370-1375, Canberra, Australia, 8-12 Dec. 2003

Computer Science

Artificial Intelligence

6 pages, 3 figures, at http://alfa.ist.utl.pt/~cvrm/staff/vramos/ref_45.html

Scientific paper

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: Swarm Intelligence, Ant Systems, Stigmergy, Data-Mining, Exploratory Data Analysis, Image Retrieval, Continuous Classification.

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