Web document clustering: a feasibility demonstration
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
WebCluster, a tool for mediated information access (demonstration abstract)
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
An Evolutionary Immune Network for Data Clustering
SBRN '00 Proceedings of the VI Brazilian Symposium on Neural Networks (SBRN'00)
A negative selection algorithm for classification and reduction of the noise effect
Applied Soft Computing
Document clustering based on modified artificial immune network
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
A novel ant-based clustering approach for document clustering
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
International Journal of Computational Vision and Robotics
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It has recently been shown that artificial immune systems (AIS) can be successfully used in many machine learning tasks. The aiNet, one such AIS algorithm exploiting the biologically-inspired features of the immune system, performs well on elementary clustering tasks. This paper proposes the use of the aiNet to more complex tasks of document clustering. Based on the immune network and affinity maturation principles, the aiNet performs an evolutionary process on the raw data, which removes data redundancy and retrieves good clustering results. Also, Principal Component Analysis is integrated into this method to reduce the time complexity. The results are compared with some classical document clustering methods - Hierachical Agglomerative Clustering and K-means.