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  • 标题:Data extraction and annotation based on domain-specific ontology evolution for deep web
  • 本地全文:下载
  • 作者:Kerui Chen ; Zuo Wanli ; He Fengling
  • 期刊名称:Computer Science and Information Systems
  • 印刷版ISSN:1820-0214
  • 电子版ISSN:2406-1018
  • 出版年度:2011
  • 卷号:8
  • 期号:3
  • 页码:673-692
  • DOI:10.2298/CSIS101011023K
  • 出版社:ComSIS Consortium
  • 摘要:

    Deep web respond to a user query result records encoded in HTML files. Data extraction and data annotation, which are important for many applications, extracts and annotates the record from the HTML pages. We proposed an domain-specific ontology based data extraction and annotation technique; we first construct mini-ontology for specific domain according to information of query interface and query result pages; then, use constructed mini-ontology for identifying data areas and mapping data annotations in data extraction; in order to adapt to new sample set, mini-ontology will evolve dynamically based on data extraction and data annotation. Experimental results demonstrate that this method has higher precision and recall in data extraction and data annotation.

  • 关键词:Deep Web; Data Extraction; Data Annotation; Domain Ontology; Ontology Evolution
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