基于图模型的关键词提取算法研究  

Study on Keyword Extraction Algorithm Based on Graphical Model

作　　者：叶子诚 闫桂英[1,2] YE Zicheng;YAN Guiying(Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190;University of Chinese Academy of Sciences,Beijing 100049)

机构地区：[1]中国科学院数学与系统科学研究院,北京100190 [2]中国科学院大学,北京100049

出　　处：《系统科学与数学》2021年第4期967-975,共9页Journal of Systems Science and Mathematical Sciences

基　　金：国家自然科学基金(11631014)资助课题。

摘　　要：自动抽取关键词技术应用广泛.文章将文本抽象成一个图模型,结合经典的TF-IDF算法和TextRank算法,利用图上的随机游走算法实现排序.以互联网上的新闻文本为数据进行了实验,结果显示该算法效果较传统的关键词提取算法更优.Keyword automatic extraction algorithm has wide application.This paper abstracts the text into a graphical model,combines classical TF-IDF algorithm and TextRank algorithm and uses the random walk algorithm on the graph to rank the nodes.Experiment is conducted based on the news text data form Internet.The results show that the algorithm has better effect than that of traditional keyword extraction algorithm.

关 键 词：提取 图模型 随机游走算法 TF-IDF算法 TextRank算法 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]