Method | Description | |
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ExtractKeyword ( string paper, int MinSupport = 5, int MaxSupport = 50, bool isSplitter = false ) : KeywordSupport[] |
对单篇文章进行关键词提取,当词的数量小于300时使用TextRank,否则使用WordCount
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ExtractSingleKeyword ( string Texts, int MinSupport = 5, int MaxSupport = 50, int MinTxtLength = 33, bool isSplitter = false ) : KeywordSupport[] |
提取关键词(单词)
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Method | Description | |
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TextRankExtract ( string spliteWords ) : int>.Dictionary |
使用TextRank算法来对关键词打分,在原有算法的得分上乘以13来和统计得分相接近
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WordCountExtract ( string spliteWords ) : int>.Dictionary |
针对词频进行统计来对关键词进行排序
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public static ExtractKeyword ( string paper, int MinSupport = 5, int MaxSupport = 50, bool isSplitter = false ) : KeywordSupport[] | ||
paper | string | 文本或者分词后结果 |
MinSupport | int | 最小得分 |
MaxSupport | int | 最大得分 |
isSplitter | bool | 是否分词 |
return | KeywordSupport[] |
public static ExtractSingleKeyword ( string Texts, int MinSupport = 5, int MaxSupport = 50, int MinTxtLength = 33, bool isSplitter = false ) : KeywordSupport[] | ||
Texts | string | 文本集,未进行分词 |
MinSupport | int | 所选词的最小支持度 |
MaxSupport | int | 所选词的最大支持度 |
MinTxtLength | int | 最小分词长度 |
isSplitter | bool | 是否已分词 |
return | KeywordSupport[] |