中圖分類號： TN02；TP391 文獻(xiàn)標(biāo)識碼： A DOI：10.16157/j.issn.0258-7998.200488 中文引用格式： 季曹婷，馬偉鋒，樓姣，等. 融合多特征TFIDF文本分析的汽車造型需求提取方法[J].電子技術(shù)應(yīng)用，2021，47(2)：16-19，27. 英文引用格式： Ji Caoting，Ma Weifeng，Lou Jiao，et al. An extraction method of car styling requirements by integrating multifeature TFIDF text analysis[J]. Application of Electronic Technique，2021，47(2)：16-19，27.
An extraction method of car styling requirements by integrating multi-feature TFIDF text analysis
Ji Caoting，Ma Weifeng，Lou Jiao，Ma Laibin
School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023，China
Abstract： In order to extract user requirements effectively in the field of car styling intelligent design, a method for extracting car styling requirements based on multi-feature TFIDF(word frequency-inverse file frequency) text analysis is proposed. Firstly, a large number of unregistered professional vocabularies is obtained through mutual information and boundary degrees of freedom to optimize the vocabulary after simple word segmentation. Next, in order to solve the problem of the limitations of the classic TFIDF algorithm, vocabulary and emotional feature factors are introduced to get user demand feature candidates set. Finally, effective user needs are obtained according to the threshold. The experimental results show that the multi-feature TFIDF text analysis algorithm has certain advantages in feature extraction, and can effectively extract user needs of the car styling in the text.
Key words : car styling；user needs analysis；keyword extraction；TFIDF
