The query mapping task that we address in this chapter is the following. Given a query submitted to a search engine, identify the concepts that are intended by the user issuing the query, where the concepts are taken from a structured knowledge base. We address our task in the setting of a digital archive, specifically, the Netherlands Institute for Sound and Vision (“Sound and Vision”). Sound and Vision maintains a large digital audiovisual collection, currently containing over a million objects and updated daily with new television and radio broadcasts. Users of the archive’s search facilities consist primarily of media professionals who use the online search interface to locate audiovisual items to be used in new programs such as documentaries and news reviews. The contents of the audiovisual items are diverse and cover a wide range of topics, people, places, and more. Furthermore, a significant part (around 50%) of the query terms are informational; consisting of either general keywords or proper names .
Because of its central role in the LOD initiative, our knowledge source of choice for semantic query suggestion is DBpedia. Thus, in practical terms, the task we are facing is: given a query (within a session, for a given user), produce a ranked list of concepts from DBpedia that are intended by the query. These concepts can then be used, for example, to suggest relevant multimedia items associated with each concept, to suggest linked geodata from the LOD cloud, or to suggest contextual information, such as text snippets from a Wikipedia article.