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Personalized information service agents have emerged in the recent years to help users to cope with the increasing amount of information available on the Internet. The effectiveness of agents depends mainly on profile completeness and accuracy. In the existing agents, although the performance of these systems improves after learning a user profile, it is(More)
It is a challenging task to identify sentiments (the affective parts of options) of reviews. One of the most important problems is to predict the sentiment orientation of the words. This paper proposes a new method for determining the sentiment orientation of the Chinese words by using bilingual lexicons. Given a Chinese word, we observe the occurrences of(More)
This paper presents a phrase pattern-based method in classifying sentiment orientation of text. That is to analyze whether the text expresses a favorable or unfavorable sentiment for a specific subject. In our method, we construct some phrase patterns and calculate their sentiment orientation by unsupervised learning algorithm. When we classify a document,(More)
BACKGROUND Analysis of gene expression data for tumor classification is an important application of bioinformatics methods. But it is hard to analyse gene expression data from DNA microarray experiments by commonly used classifiers, because there are only a few observations but with thousands of measured genes in the data set. Dimension reduction is often(More)
It is becoming common that people browse Web for product reviews before purchasing. However, to retrieve opinions relevant to customer desire still remains challenging. In this paper, we studied the problem of opinion searching, whose aim is to search the opinions about specific feature of specific product and locate them in multi-product reviews. Our(More)
This paper introduces an effective mesh smoothing method for 3D noisy shapes via the adaptive MMSE (minimum mean squared error) filter. The adaptive MMSE filter is applied to modify the face normals of triangle meshes and then mesh vertex positions are reconstructed in order to satisfy the modified normals. We also compare quantitatively and visually the(More)
It is hard to analyse gene expression data which has only a few observations but with thousands of measured genes. Partial Least Squares based Dimension Reduction (PLSDR) is superior for handling such high dimensional problems, but irrelevant features will introduce errors into the dimension reduction process. Here, feature selection is applied to filter(More)
The different effects of input attributes on category results in supervised ART (adaptive resonance theory) network is quite important during the predictive stage in the application that was ignored by the traditional researches. In fact, some of the attributes have larger effect than the others on category results, but, even for the experts in that field,(More)