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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Schenkel, R., & Theobald, M. (2006). Structural feedback for keyword-based XML retrieval. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3936 LNCS, pp. 326–337). Springer Verlag. https://doi.org/10.1007/11735106_29
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