Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Mining massive document collections by the WEBSOM method
Information Sciences: an International Journal - Special issue: Soft computing data mining
Active Hypercontours and Contextual Classification
ISDA '05 Proceedings of the 5th International Conference on Intelligent Systems Design and Applications
WImBI'06 Proceedings of the 1st WICI international conference on Web intelligence meets brain informatics
Active contours as knowledge discovery methods
DS'07 Proceedings of the 10th international conference on Discovery science
MP-Boost: a multiple-pivot boosting algorithm and its application to text categorization
SPIRE'06 Proceedings of the 13th international conference on String Processing and Information Retrieval
Adaptive potential active hypercontours
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Self organization of a massive document collection
IEEE Transactions on Neural Networks
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Together with fast development of different areas of Pattern Analysis, an increasing demand on new models and techniques is observed. Especially new Information Retrieval tasks, oriented on data meaning rather than layout, prove to be demanding for most known techniques. Neuronal Group Learning concept presented in this article, together with prototype implementation gives flexibility of utilization of any kind of expert knowledge about the problem to ease classifier inference process. It can also be used to acquire structural knowledge about an object, which can later be used for solving a segmentation problem- often addressed in semantics-oriented text and image processing.