Structural feedback for keyword-based XML retrieval

被引:0
|
作者
Schenkel, Ralf [1 ]
Theobald, Martin [1 ]
机构
[1] Max Planck Inst Informat, Saarbrucken, Germany
来源
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暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Keyword-based queries are an important means to retrieve information from XML collections with unknown or complex schemas. Relevance Feedback integrates relevance information provided by a user to enhance retrieval quality. For keyword-based XML queries, feedback engines usually generate an expanded keyword query from the content of elements marked as relevant or nonrelevant. This approach that is inspired by text-based IR completely ignores the semistructured nature of XML. This paper makes the important step from pure content-based to structural feedback. It presents a framework that expands a keyword query into a full-fledged content-and-structure query. Extensive experiments with the established INEX benchmark and our TopX search engine show the feasibility of our approach.
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页码:326 / 337
页数:12
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