Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Self-Organizing Maps
A supervised training algorithm for self-organizing maps for structures
Pattern Recognition Letters - Special issue: Artificial neural networks in pattern recognition
A self-organizing map for adaptive processing of structured data
IEEE Transactions on Neural Networks
Efficient Clustering of Structured Documents Using Graph Self-Organizing Maps
Focused Access to XML Documents
Ranking Web Pages Using Machine Learning Approaches
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
A weighted common structure based clustering technique for XML documents
Journal of Systems and Software
Clust-XPaths: clustering of XML paths
MLDM'11 Proceedings of the 7th international conference on Machine learning and data mining in pattern recognition
A flexible structured-based representation for XML document mining
INEX'05 Proceedings of the 4th international conference on Initiative for the Evaluation of XML Retrieval
Hi-index | 0.00 |
Self-Organizing Maps capable of encoding structured information will be used for the clustering of XML documents. Documents formatted in XML are appropriately represented as graph data structures. It will be shown that the Self-Organizing Maps can be trained in an unsupervised fashion to group XML structured data into clusters, and that this task is scaled in linear time with increasing size of the corpus. It will also be shown that some simple prior knowledge of the data structures is beneficial to the efficient grouping of the XML documents.