利用本体关联度改进的TF-IDF特征词提取方法

Improved TF-IDF Feature Selection Method Based on Ontology Relative Degree

针对传统TF-IDF方法提取文本特征词时未考虑词语间关系的不足,提出一种利用本体关联度改进的文本特征词提取方法。该方法首先利用传统的TF-IDF方法构建候选特征词集合和非候选特征词集合,然后根据领域本体知识在非候选特征词集合中提取候选特征词的本体关联词,利用候选特征词与其本体关联词之间的本体关联度以及本体关联词本身的权重调整候选特征词的权重,得到新的候选特征词权重排序。实验证明,该方法能够有效提高文本特征词提取的准确度。

A method of improved feature extraction based on Ontology was proposed to compensate for the weakness of Traditional TF-IDF that Traditional TF-IDF does not consider the relation between the words.This method gets a set of candidate feature words which are the previous n words and a set of non-candidate feature words by Traditional TF-IDF,and gets a set of ontology associated concepts by the ontology relative degree;last,adjusts the weights of the feature keys by the ontology relative degree and the weights of ontology relative terms,and obtain the new results.The experimental results display that the new method improves the accuracy of feature extraction.