Information Integration for the Masses

Jim Blythe (USC Information Sciences Institute, USA)

Dipsy Kapoor (USC Information Sciences Institute, USA)

Craig A. Knoblock (USC Information Sciences Institute, USA)

Kristina Lerman (USC Information Sciences Institute, USA)

Steven Minton (Fetch Technologies, USA)

Abstract: 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.

Keywords: assistants, information extraction, web applications

Categories: D.2.11, H.3.5, H.3.6, H.3.7