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In this demonstration paper we present MAPS, a novel system that combines approximate information retrieval and filtering functionality in a peer-to-peer setting. In MAPS, a user is able to submit one-time and continuous queries, and receive matching resources and notifications from selected information sources. The selection of these sources in the retrieval case is based on well-known resource selection techniques for peer-to-peer query routing, while in the filtering case a combination of resource selection and novel behavior prediction techniques using time-series analysis of publisher statistics is used. The integration of the two functionalities is done in a seamless way utilizing the same machinery: a conceptually global, but physically distributed directory of statistics about information sources based on distributed hash tables.