Schema Mapping in P2P Networks Based on Classification and Probing

In this paper, we address the problems of adaptive schema mappings between different peers in peer-to-peer network and searching for interesting data residing at different peers based on such mappings. We begin by classifying the shared schema of each peer into a taxonomy of relation categories and attribute categories. We then propose our adaptive schema mapping by selectively probing the shared schema with query probes, which are generated by the classification rules. To improve the accuracy of schema mapping, we introduce the notion of confusion matrix and prior-knowledge. Finally, we present the query reformulation strategy for retrieving and integrating data from all relevant peers. We have implemented our proposed schema mapping and query processing methods in real settings with real datasets. The experimental results show that our method can be adopted effectively in practice.