This paper proposes a novel approach to integrating heterogeneous XML DTDs. With this approach, an information agent can be easily extended to integrate heterogeneous XML-based contents and perform federated search. Based on a tree grammar inference technique, this approach derives an integrated view of XML DTDs in an information integration framework. The derivation takes advantages of naming and structural similarities among DTDs in similar domains. The complete approach consists of three main steps. (1) DTD clustering clusters DTDs in similar domains into classes. (2) Schema learning applies a tree grammar inference technique to generate a set of tree grammar rules from the DTDs in a class from the previous step. (3) Minimization optimizes the rules generated in the previous step and transforms them into an integrated view. We have implemented the proposed approach into a system called DEEP and tested the system on artificial and real domains. The experimental results reveal that this system can effectively and efficiently integrate radically different DTDs.
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