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Conference Paper

Relevance Feedback for Structural Query Expansion


Schenkel,  Ralf
Databases and Information Systems, MPI for Informatics, Max Planck Society;

Theobald,  Martin
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Schenkel, R., & Theobald, M. (2006). Relevance Feedback for Structural Query Expansion. In Advances in XML Information Retrieval and Evaluation, 4th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2005 (pp. 344-357). Berlin, Germany: Springer.

Cite as:
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 two independent approaches that include structural dimensions in a feedback-driven query evaluation: The first approach reranks the result list of a keyword-based search engine, using structural features derived from results with known relevance. The second approach expands a keyword query into a full-fledged content-and-structure query with weighted conditions.