A Knowledge-Based Approach for Selecting Information Sources
Thomas Eiter, Michael Fink, and Hans Tompits

TL;DR
This paper introduces a knowledge-based system using extended logic programs to select appropriate information sources for query answering, effectively handling heterogeneous data and user preferences.
Contribution
It presents a novel declarative approach with formal semantics for source selection using extended logic programs, including a prototype implementation and experimental evaluation.
Findings
Effective source selection for heterogeneous data sources.
Formal semantics for source-selection programs.
Prototype implementation demonstrating practical applicability.
Abstract
Through the Internet and the World-Wide Web, a vast number of information sources has become available, which offer information on various subjects by different providers, often in heterogeneous formats. This calls for tools and methods for building an advanced information-processing infrastructure. One issue in this area is the selection of suitable information sources in query answering. In this paper, we present a knowledge-based approach to this problem, in the setting where one among a set of information sources (prototypically, data repositories) should be selected for evaluating a user query. We use extended logic programs (ELPs) to represent rich descriptions of the information sources, an underlying domain theory, and user queries in a formal query language (here, XML-QL, but other languages can be handled as well). Moreover, we use ELPs for declarative query analysis and…
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Taxonomy
TopicsSemantic Web and Ontologies · Logic, Reasoning, and Knowledge · Advanced Database Systems and Queries
