摘要： 以Web页面信息项本体定义为基础，对单个样本页面信息项路径进行启发式学习，对所有样本页面集中信息块路径进行归纳学习，识别结构相似的信息块子树位置，以准确划定信息抽取区域，降低页面噪声。将经过噪声处理的样本页面自动解析成页面的结构本体。比较Web页面信息项本体和页面的结构本体，通过归纳学习算法生成抽取规则，提高Web信息的抽准率。

关键词: 信息抽取, 本体, 归纳学习, 文档对象模型

Abstract: On basis of definition of information item ontology for Web page, the heuristic learning is conducted for information items in sole sample Web page, and inductive learning is conducted for the path of information blocks in whole sample Web collection. A method for researching the path of Document Object Model(DOM) tree is proposed. Using this method, the location of the structured-like information block subtrees can be got, the areas of information extraction can be partition accurately. The construction ontology by automatic parsing the Web page filtering the noise is created. Compared the information item ontology with the construction ontology, the information extraction rules by using reconstructing inductive learning arithmetic are generated. The precision of information extraction is improved.

Key words: information extraction, ontology, inductive learning, Document Object Model(DOM)

中图分类号: 

• N945