Prose and Poetry Classification and Boundary Detection Using Word Adjacency Network Analysis

作     者：Mrowinski, Maciej J. Kosinski, Robert A. 

作者机构：Warsaw Univ Technol Fac Phys PL-00662 Warsaw Poland Natl Res Inst Cent Inst Labour Protect PL-00701 Warsaw Poland 

出 版 物：《INTERNATIONAL JOURNAL OF MODERN PHYSICS C》 (国际现代物理学杂志，C: 计算物理学和物理计算)

年 卷 期：2010年第21卷第4期

页      面：513-522页

核心收录：

学科分类：07[理学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 0702[理学-物理学] 

基　　金：University of the Phillippines Office 

主　　题：Text genre classification word adjacency networks LDA Structures and organization in complex systems Complex systems Computer science and technology 

摘      要：Word adjacency networks constructed from written works reflect differences in the structure of prose and poetry. We present a method to disambiguate prose and poetry by analyzing network parameters of word adjacency networks, such as the clustering coefficient, average path length and average degree. We determine the relevant parameters for disambiguation using linear discriminant analysis (LDA) and the effect size criterion. The accuracy of the method is 74.9 +/- 2.9% for the training set and 73.7 +/- 6.4% for the test set which are greater than the acceptable classifier requirement of 67.3%. This approach is also useful in locating text boundaries within a single article which falls within a window size where the significant change in clustering coefficient is observed. Results indicate that an optimal window size of 75 words can detect the text boundaries.