A Semi—Structured Document Model for Text Mining  

作　　者：杨建武 陈晓鸥 

机构地区：[1]NationalKeyLaboratoryforTextProcessing,InstituteofComputerScienceandTechnologyPekingUniversity,Beijing100871,P.R.China [2]NationalKeyLaboratoryforTextProcessing,InstituteofComputerScienceandTechnologyPek

出　　处：《Journal of Computer Science & Technology》2002年第5期603-610,共8页计算机科学技术学报（英文版）

基　　金：国家技术创新工程及北京大学校科研和教改项目

摘　　要：A semi-structured document has more structured information compared to anordinary document, and the relation among semi-structured documents can be fully utilized. Inorder to take advantage of the structure and link information in a semi-structured document forbetter mining, a structured link vector model (SLVM) is presented in this paper, where a vectorrepresents a document, and vectors' elements are determined by terms, document structure andneighboring documents. Text mining based on SLVM is described in the procedure of K-meansfor briefness and clarity: calculating document similarity and calculating cluster center. Theclustering based on SLVM performs significantly better than that based on a conventional vectorspace model in the experiments, and its F value increases from 0.65-0.73 to 0.82-0.86.

关 键 词：HTML语言 XML语言 半结构文件模型 版本开采 结构信息 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]