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Ontology learning is from a given area document sets automatic or semi-automatic extraction terms to construct a domain ontology. Area concept extraction is one of the most important aspects in building ontology. In this paper, we proposed an improved area concept extraction algorithm. In the algorithm, we firstly employed association rule algorithm to obtain the similarity between the sememes, and...
This paper presents a PSO-based method for learning similarity measure of nominal features for case based reasoning classifiers (i.e. CBR classifiers). The symbolic features considered here takes completely unordered values. It has been indicated in that in specific classification task, the similarities between these nominal feature values can not be simply considered as either 0 or 1. A GA-based...
Decision tree algorithm is not only the important part of machine learning, but also the most widely used data mining tool. At present, there are many algorithms of generating decision tree, but when the database which we rely on exists noise, high quality knowledge is hard to obtain by ID3 algorithm. In this paper, we propose the data mining method based on second learning in case of ID3 algorithm,...
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