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With the current explosion of data, retrieving and integrating information from various sources is a critical problem. Work in multidatabase systems has begun to address this problem, but it has primarily focused on methods for communicating between databases and requires significant effort for each new database added to the system. This paper describes a more general approach that exploits a semantic model of a problem domain to integrate the information from various information sources. The information sources handled include both databases and knowledge bases, and other information sources (e.g. programs) could potentially be incorporated into the system. This paper describes how both the domain and the information sources are modeled, shows how a query at the domain level is mapped into a set of queries to individual information sources, and presents algorithms for automatically improving the efficiency of queries using knowledge about both the domain and the information sources. This work is implemented in a system called SIMS and has been tested in a transportation planning domain using nine Oracle databases and a Loom knowledge base.

UC is a natural language help facility which advises users in using the UNIX operating system. Users can query UC about how to do things, command names and formats, online definitions of UNIX or general operating systems terminology, and debugging problems in using commands. UC is comprised of the following components: a language analyzer and generator, a context and memory model, an experimental common-sense planner, highly extensible knowledge bases on both the UNIX domain and the English language, a goal analysis component, and a system for acquisition of new knowledge through instruction in English. The language interface of UC is based on a “phrasal analysis” approach which integrates semantic, grammatical and other types of information. In addition, it includes capabilities for ellipsis resolution and reference disambiguation.

Abstract. The standard approach t o i n tegrating heterogeneous information sources is to build a global schema that relates all of the information in the di erent sources, and to pose queries directly against it. The problem is that schema integration is usually di cult, and as soon as any of the information sources change or a new source is added, the process may h a ve to be repeated.The SIMS system uses an alternative approach. A domain model of the application domain is created, establishing a xed vocabulary for describing data sets in the domain. Using this language, each a vailable information source is described. Queries to SIMS against the collection of available information sources are posed using terms from the domain model, and reformulation operators are employed to dynamically select an appropriate set of information sources and to determine how t o i n tegrate the available information to satisfy a query. This approach results in a system that is more exible than existing ones, more easily scalable, and able to respond dynamically to newly available or unexpectedly missing information sources. This paper describes the query reformulation process in SIMS and the operators used in it. We p r o vide precise de nitions of the reformulation operators and explain the rationale behind choosing the speci c ones SIMS uses. We h a ve demonstrated the feasibility and e ectiveness of this approach b y applying SIMS in the domains of transportation planning and medical trauma care.