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首页> 外文期刊>ITB Journal of Information and Communication Technology >Free Model of Sentence Classifier for Automatic Extraction of Topic Sentences
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Free Model of Sentence Classifier for Automatic Extraction of Topic Sentences

机译:用于自动提取主题句子的句子分类器免费模型

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This research employs free model that uses only sentential features without paragraph context to extract topic sentences of a paragraph. For finding optimal combination of features, corpus-based classification is used for constructing a sentence classifier as the model. The sentence classifier is trained by using Support Vector Machine (SVM). The experiment shows that position and meta-discourse features are more important than syntactic features to extract topic sentence, and the best performer (80.68%) is SVM classifier with all features.
机译:这项研究采用了免费模型,该模型仅使用没有段落上下文的句子特征来提取段落的主题句子。为了找到特征的最佳组合,基于语料库的分类用于构建句子分类器作为模型。句子分类器通过使用支持向量机(SVM)进行训练。实验表明,位置和元语篇特征比句法特征对提取主题句更为重要,表现最佳的是支持所有特征的SVM分类器,占80.68%。

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