摘要：Information integration applications combine data from heterogeneous sources to assist the user in solving repetitive data-intensive tasks. Currently, such applications require a high level of expertise in information integration since users need to know how to extract data from an on-line source, describe its semantics, and build integration plans to answer specific queries. We have integrated three task learning technologies within a single desktop application to assist users in creating information integration applications. It includes a tool for programmatic access to data in on-line information sources, a tool to semantically model them by aligning their input and output parameters with a common ontology, and a tool that enables the user to create complex integration plans using simple text instructions. Our system was integrated within the Calo Desktop Assistant and evaluated independently on a range of problems. It enabled non-expert users to construct integration plans for a variety of problems in the office and travel domains.
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