Structural Feedback for Keyword-Based XML Retrieval

Abstract

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.