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Keywords Extraction Based on Text Classification

机译:基于文本分类的关键词提取

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In this paper, we propose new keywords extraction method based on texts classification. We first classify texts to determine their categories. Then determine weights of candidate words according to both their frequency and the relevance between text words and text category. Finally, keywords are extracted by sorting weights of candidate words. We conduct this experiment to show that on the premise of accurate text classification, this method can extract keywords effectively from text without title or with deviated title which can not reflect text's subject. Objective selecting of candidate word weighting function still needs to be further researched.
机译:本文提出了一种新的基于文本分类的关键词提取方法。我们首先对文本进行分类以确定其类别。然后根据候选词的出现频率和文本词与文本类别的相关性来确定候选词的权重。最后,通过对候选词的权重排序来提取关键词。我们通过实验证明,在准确分类的前提下,该方法可以有效地从没有标题或标题偏离的文本中提取关键词,而这些文本不能反映文本的主题。候选词权重函数的客观选取还有待进一步研究。

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