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Opinion mining is an important research area of web data mining. As it is related to natural language process and data mining, opinion mining is very challenging. This paper presents a web opining mining algorithm based on sentiment phrase classification vector. By the techniques of sentiment phrase classification, the algorithm compares the similarity between document vectors, mines the theme of...
Our aim in this paper is to propose a rule-weight learning algorithm in fuzzy rule-based classifiers. The proposed algorithm is presented in two modes: first, all training examples are assumed to be equally important and the algorithm attempts to minimize the error-rate of the classifier on the training data by adjusting the weight of each fuzzy rule in the rule-base, and second, a weight is assigned...
The Partitioned Feature-based Classifier (PFC) is proposed in this paper. PFC does not use entire feature vectors extracted from the original data at once to classify each datum, but use only groups of features related to each feature vector to classify data separately. In the training stage, the contribution rate calculated from each feature vector group is drawn throughout the accuracy of each feature...
In this paper, a novel hierarchical speaker verification method based on PCA classifier and kernel fisher discriminant (KFD) classifier was proposed. Firstly, we gota coarse decision by a fast scan all registered speakers using PCA classifier to find R possible target speakers, and then KFD classifier was used to make final decision. PCA also has another advantage: reduction of the feature vectors...
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