计算机工程2017，Vol.43Issue(6)：118-124,7.DOI:10.3969/j.issn.1000-3428.2017.06.020
基于知识图谱的Web信息抽取系统
Web Information Extraction System Based on Knowledge Graph
摘要
Abstract
In order to effectively extract huge amounts of Web information in multiple fields,a Web information extraction system is designed based on Chinese knowledge graph,CN-DBpedia.Firstly,webpage data items with noise are automatically labeled based on knowledge graph.Then,correct wrappers are induced and learned from labeling sets with errors by a fault-tolerant wrapper induction framework.Experimental results demonstrate that,compared with traditional information extraction method by manual annotation,the proposed system has higher precision and recall rate.It can significantly reduce human participation during the extraction process and flexibly apply to large-scale webpage information extraction tasks in multiple fields.关键词
知识图谱/多领域/Web信息抽取/网页自动标注/容错/包装器归纳框架Key words
knowledge graph/multi-field/Web information extraction/automatic webpage labeling/fault-tolerance/wrapper induction framework分类
信息技术与安全科学引用本文复制引用
王辉,郁波,洪宇,肖仰华..基于知识图谱的Web信息抽取系统[J].计算机工程,2017,43(6):118-124,7.基金项目
上海市科技创新行动计划基础研究项目(15JC1400900) （15JC1400900）
上海市自然科学基金(13ZR1417700). （13ZR1417700）
