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For each aspect, relevant segments with their relations in the resulting tree are localized and transformed into a set of features. A set of classification rules is subsequently induced and evaluated on data. The proposed framework performs well in several experimental settings, with the accuracy values ranging from 74.0% to 77.1% being achieved. 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