一種適應短文本的相關測度及其應用:針對博客社區和BBS 論壇充斥Web 垃圾信息的問題，提出相關度向量空間模型cVSM，并以此作為評論的特征，采用支持向量
機分類算法自動識別垃圾評論。cVSM 包括一種適合短文本的相關測度，用于衡量評論和文章的語義相關程度。在中文博客測試集和中文
BBS 測試集上的實驗結果表明，相比純粹使用評論文本特征的方法，應用該模型時F1 至少提高6%。
關鍵詞：博客；垃圾評論；支持向量機；文本挖掘；相關測度
Relevancy Coefficient and Its Application Adapted to Short Texts
HE Hai-jiang
(Computer Center, Changsha University, Changsha 410003)
【Abstract】A relevancy coefficient vectort space model named cVSM is proposed to aim at Web spams which flood in blogosphere and forums.
The cVSM whose components are employed as features of comments and the support vector machine classification algorithms are used to
automatically identify comment spams. The relevancy coefficient included in the cVSM is presented, which is used to evaluate relevancy grade of
posts and comments. Chinese blog dataset and Chinese BBS dataset are tested. Experimental results show that compared with traditional method the
F1 has been improved at least 6% by this way.
【Key words】blog; comment spam; support vector machine; text mining; relevancy coefficient