Multi-feature keyword extraction method based on TF-IDF and Chinese grammar analysis

In order to solve the problem of over-dependence on word frequency in traditional TF-IDF algorithm, a multi-feature keyword extraction method combined with grammar analysis is proposed. By integrating the features of grammatical information, part of speech and word position, the method constructs a grading and weighting process for candidate keywords that takes into account various influencing factors comprehensively, and makes use of the grammatical information in the sentence to perform keyword sorting optimization operation to form the formally extracted keywords. The experimental results show that the proposed method is better than the traditional method, and can improve the problem of over-dependence on word frequency and extract satisfactory keywords.