In this paper, we are interested in aggregated search in XML documents. Our goal is to retrieve the best set of XML elements to be returned. We present a structured information retrieval model based on the Bayesian networks theory. The networks structure provides a natural representation of links between a document, its elements, and its contents. In this model, the user's query starts a propagation process to recover the XML elements. Thus, instead of retrieving a whole document or a list of disjoint elements that are likely to answer partially the query, we attempt to build a virtual document that aggregates a set of elements that are relevant and complementary. We evaluated our approach using the INEX 2009 collection and presented some empirical results for evaluating the impact of the aggregation approach.
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