句法复杂网络作为语体分类的知识源研究  

Using syntactic network characteristics to do text clustering

作　　者：陈芯莹[1] 刘海涛[2] 

机构地区：[1]西安交通大学外国语学院,西安710049 [2]浙江大学语言行为模式中心,杭州310058

出　　处：《计算机工程与应用》2013年第8期32-36,共5页Computer Engineering and Applications

基　　金：国家社会科学基金重大项目(No.11&ZD188)

摘　　要：基于6种语体的句法树库构建了6个依存句法网络,对这些网络的边数、节点数、节点平均度、聚类系数、平均最短路径长度、网络中心势、直径、节点度幂律分布的幂指数、度分布与幂律拟合的决定系数等整体特征进行了对比分析。以这些整体特征为变量,采用欧几里德的"最短距离"法,对这6种语体的句法网络进行了聚类分析。研究结果显示,通过一些网络的主要参数,即网络节点数、聚集系数、平均路径长度、中心势以及节点度幂律分布的幂指数,可以对所研究的文本进行分类。与传统的文本聚类方法相比,其结果更容易从语言学的角度进行合理的解释。This paper builds six dependence syntactic networks based on six treebanks of different styles and gives a comparative analysis of overall characteristics of the networks, including the number of edges, the number of the nodes, the average degree, the clustering coefficient, the average path length, the centralization, the diameter, and the index of power-law, coefficient of determination. After that, the paper uses the Euclidean ＂the shortest distance＂ method, with characteristics as variables, to do clustering analysis of these networks. The results show that using some main parameters of networks, namely the number of the nodes, the clustering coefficient, the average path length, the centralization and the index of power-law, can do cluster analysis on texts. Compared with the traditional text clustering, the results are easier to explain in linguistic angle.

关 键 词：语体 文本分类 网络特征 语言网络 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]