The dynamics of collective sorting robot-like ants and ant-like robots
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Diversity and adaptation in populations of clustering ants
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Modern Information Retrieval
On the performance of ant-based clustering
Design and application of hybrid intelligent systems
Ant-Based Clustering and Topographic Mapping
Artificial Life
Dynamic decentralized any-time hierarchical clustering
ESOA'06 Proceedings of the 4th international conference on Engineering self-organising systems
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The self-organizing and autonomous behavior of social insects such as ants presents an interesting and powerful metaphor for applications in the retrieval and management of large and fast growing amount of online information. The explosive growth of web documents has increasingly made more difficult and costly the manual task of organizing the documents into meaningful categories by human experts. Hence, it is desirable that some degree of automation be incorporated into the classification process to enable better scalability and prevent human classifiers from being overwhelmed by the deluge of information. This paper presents a preliminary investigation of applying a homogeneous multi-agent clustering system based on the self-organization behavior of the ants to the high-dimensional problem of web document categorization. A description of the text processing needed to obtain significant document features is included. The system will be evaluated on multi-class online English documents obtained from a popularly used search engine.