【摘要】 在关键词抽取方法研究中,提出了多步骤的,针对任意领域的文本关键词抽取方法。该方法采用多元文法进行候选关键词抽取,提出了基于语言学特征的扩展tf/idf关键词的加权计算方法,以及能够抽取未登录词的关键词的方法和对关键词抽取进行优化的策略。首次提出了用支持向量机对最后的抽取结果进行优化。实验结果表明,该方法与单纯的tf/idf算法相比,具有更高的查准率和查全率。更多还原

【Abstract】 In keyword extraction approach, a new keyword extraction method is proposed based on tf/idf with multi-strategies for any field documents. Using n-grams extract a bag of keyword candidate, and then define the rational features according to their morphological characters and context information. Moreover, several strategies is proposed to amend the incomplete words gotten from the word segmentation and find unknown potential Keywords. Using support vector machines to improve the results of keyword extraction is proposed. The experimental result show that the proposed method outperforms tf/idf in precision and recall更多还原