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This paper describes ongoing research into obtaining and using knowledge bases to assist information retrieval. These structures are prohibitively expensive to obtain manually, yet automatic approaches have been researched for decades with limited success. This research investigates a potential shortcut: a way to provide knowledge bases automatically, without expecting computers to replace expert human indexers. Instead we aim to replace the professionals with thousands or even millions of amateurs: with the growing community of contributors who form the core of Web 2.0. Specifically we focus on Wikipedia, which represents a rich tapestry of topics and semantics and a huge investment of human effort and judgment. We show how this can be directly exploited to provide manually-defined yet inexpensive knowledge-bases that are specifically tailored to expose the topics, terminology and semantics of individual document collections. We are also concerned with how best to make these structures available to users, and aim to produce a complete knowledge-based retrieval system-both the knowledge base and the tools to apply it-that can be evaluated by how well it assists real users in performing realistic and practical information retrieval tasks. To this end we have developed Koru, a new search engine that offers concrete evidence of the effectiveness of our Web 2.0 based techniques for assisting information retrieval.