The enhancement of TextRank algorithm by using word2vec and its application on topic extraction

2nd Annual International Conference on Information System and Artificial Intelligence

物理学;计算机科学

Zuo, Xiaolei^1 ; Zhang, Silan^1,2 ; Xia, Jingbo^2,3,4

College of Science, Huazhong Agricultural University, Wuhan, China^1

Institute of Applied Mathematics, Huazhong Agricultural University, Wuhan, China^2

College of Informatics, Huazhong Agricultural University, Wuhan, China^3

Hubei Key Laboratory of Agricultural Bioinformatics, Wuhan, China^4

关键词: ITS applications;    Key word matching;    Model comparison;    Semantic similarity;    Simulation tests;    Topic extraction;    Word embedding;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/887/1/012028/pdf
DOI  :  10.1088/1742-6596/887/1/012028

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

TextRank is a traditional method for keyword matching and topic extraction, while its drawback stems from the ignoring of the semantic similarity among texts. By using word embedding technique, Word2Vec was incorporated into traditional TextRank and four simulation tests were carried on for model comparison. The results showed that the hybrid combination of Word2Vec and TextRank algorithms achieved better keyword/topic extraction towards our testing text dataset.