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作 者:孙北宁 吕维新 曾俊 肖衡 Sun Beining;Lv Weixin;Zeng Jun;Xiao Heng(Department of Science Technology and Data,Yunnan Power Grid Co.,Ltd.,Kunming 650011,China;School of Big Data and Intelligent Engineering,Southwest Forestry University,Kunming 650224,China;Kunming Power Supply Bureau,Yunnan Power Grid Co.,Ltd.,Kunming 650011,China;Yunnan Yundian Tongfang Technology Co.,Ltd.,Kunming 650214,China)
机构地区:[1]云南电网有限责任公司科数部,云南昆明650011 [2]西南林业大学大数据与智能工程学院,云南昆明650224 [3]云南电网有限责任公司昆明供电局,云南昆明650011 [4]云南云电同方科技有限公司,云南昆明650214
出 处:《电子技术应用》2023年第6期89-93,共5页Application of Electronic Technique
基 金:国家自然科学基金项目(61702442)。
摘 要:为了提高科技项目文本相似性度量的准确性和性能,将TF-IDF和Simhash相结合,提出了一种新的科技项目文本相似性度量方法。首先,该方法对科技项目文本进行预处理得到词项集合,再使用TF-IDF计算词项集合中每个词项的权重值,并选取具有较高权重值的重要词项;其次,使用Simhash把重要词项映射为固定长度的二进制串,并求和得到文本的Simhash签名;最后,使用汉明距离计算两个Simhash签名间的相似性。实验结果表明,所提方法在查准率、召回率和F度量值方面优于传统的Simhash算法和TF-IDF方法。To enhance the accuracy and performance of text similarity measurement of science and technology projects,this pa‐per proposes a new approach for measuring text similarity of science and technology projects by combining TF-IDF and Simhash.Firstly,this method uses natural language processing technology to preprocess science and technology project texts to get a term set,then uses the TF-IDF method to calculate the TF-IDF value of each term in the term set,and selects the important term with higher TF-IDF value.Secondly,this method uses the Simhash algorithm to get the Simhash signature of the text through mapping the selected important terms into fixed binary strings.Finally,Hamming distance is used to calculate the similarity between two Simhash signatures.Experimental results show that compared to the traditional Simhash and TF-IDF,the proposed method can promote the evaluation metrics of precision,recall and F-measure.
关 键 词:科技项目文本 文本相似度 TF-IDF Simhash算法
分 类 号:TP311[自动化与计算机技术—计算机软件与理论]
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