引用格式: Chun-Yan Liang, Li Guo, Zhao-Jie Xia, Feng-Guang Nie, Xiao-Xia Li, Liang Su and Zhang-Yuan Yang, Dictionary-based text categorization of chemical web pages, Information Processing & Management, 2006, 42(4):1017-1029

标题：Dictionary-based text categorization of chemical web pages

作者: Chun-Yan Liang, Li Guo, Zhao-Jie Xia, Feng-Guang Nie, Xiao-Xia Li, Liang Su and Zhang-Yuan Yang；中国科学院过程工程研究所多相复杂系统国家重点实验室：高性能计算与化学信息学课题组

关键词: Chemistry-focused search engine; Dictionary-based text categorization; Automatic segmentation; k-NN; Latent semantic indexing; Voting

摘要：A new dictionary-based text categorization approach is proposed to classify the chemical web pages efficiently. Using a chemistry dictionary, the approach can extract chemistry-related information more exactly from web pages. After automatic segmentation on the documents to find dictionary terms for document expansion, the approach adopts latent semantic indexing (LSI) to produce the final document vectors, and the relevant categories are finally assigned to the test document by using the k-NN text categorization algorithm. The effects of the characteristics of chemistry dictionary and test collection on the categorization efficiency are discussed in this paper, and a new voting method is also introduced to improve the categorization performance further based on the collection characteristics. The experimental results show that the proposed approach has the superior performance to the traditional categorization method and is applicable to the classification of chemical web pages.