中圖分類(lèi)號(hào)： TP311
文獻(xiàn)標(biāo)識(shí)碼： A
DOI：10.16157/j.issn.0258-7998.191420
中文引用格式： 趙曉平，馬文，劉雪萍，等. 一種面向科技項(xiàng)目文本的相似度度量方法[J].電子技術(shù)應(yīng)用，2020，46(5)：31-34，39.
英文引用格式： Zhao Xiaoping，Ma Wen，Liu Xueping，et al. A similarity measurement method for science and technology project text[J]. Application of Electronic Technique，2020，46(5)：31-34，39.

A similarity measurement method for science and technology project text

Abstract： Existing text similarity measurements often use the TF-IDF method to model texts as term frequency vectors without considering the structural features of texts. This paper combines the structural features of texts with the TF-IDF method and proposes a text similarity measurement for science and technology project texts. This approach firstly pre-processes a text and extracts module texts according to its structural features. After applying the TF-IDF method to these extracted module texts, this method extracts the top keywords of each module text, obtains its feature vector representation, and finally uses cosine formula to calculate the similarity of two texts. By comparing with the TF-IDF method, experimental results show that the proposed method can promote the evaluation metrics of F-measure.

Key words : text similarity；TF-IDF；text clustering；natural language process