TCBR-HMM: An HMM-based text classifier with a CBR system
The paper presents an innovative solution to model distributed adaptive systems in biomedical environments. A Case Based Reasoning system with an original Hidden Markov Model for biomedical text classification is proposed. The model classifies scientific documents by their content, taking into account the relevance of words. The model is able to adapt to new documents in an iterative learning frame. The model is tested with the SVM and k-NN classifiers using the Ohsumed scientific collection. Empirical and statistical results show the method outperforms other efficient text classifiers.
text classification case based reasoning system hidden markov model