文章基本信息

标题：Robust and Efficient Annotation based on Ontology Evolution for Deep Web Data
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作者：Chen, Kerui ; Zuo, Wanli ; Zhang, Fan 等
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2011
卷号：6
期号：10
页码：2029-2036
DOI：10.4304/jcp.6.10.2029-2036
语种：English
出版社：Academy Publisher
摘要：Among those researches in Deep Web, compared to research of data extraction which is more mature, the research of data annotation is still at its preliminary stage. Currently, although the approach of applying ontology in data annotating has been approved by most researchers, there are many weaknesses existed, such as the complexity of the ontology, as well as the limitation on static ontology’s ability to annotate new pages. Respond to those problems, this paper proposes a robust, highly efficient data annotation method based on ontology evolution. It needs to be noticed that this paper defines a simpler ontology which can improve annotating efficiency significantly. Experiments indicate that this method could improve the accuracy and efficiency of data annotation.
关键词：Deep Web;Ontology Evolution;Data Extraction;Data Annotation