| | |
Summary: Artificial Intelligence 118 (2000) 115161
Flexible and scalable cost-based query planning
in mediators: A transformational approach
José Luis Ambite , Craig A. Knoblock
Information Sciences Institute and Department of Computer Science, University of Southern California,
4676 Admiralty Way, Marina del Rey, CA 90292, USA
Received 30 October 1998; received in revised form 11 October 1999
Abstract
The Internet provides access to a wealth of information. For any given topic or application
domain there are a variety of available information sources. However, current systems, such as
search engines or topic directories in the World Wide Web, offer only very limited capabilities
for locating, combining, and organizing information. Mediators, systems that provide integrated
access and database-like query capabilities to information distributed over heterogeneous sources,
are critical to realize the full potential of meaningful access to networked information.
Query planning, the task of generating a cost-efficient plan that computes a user query from
the relevant information sources, is central to mediator systems. However, query planning is a
computationally hard problem due to the large number of possible sources and possible orderings
on the operations to process the data. Moreover, the choice of sources, data processing operations,
and their ordering, strongly affects the plan cost.
In this paper, we present an approach to query planning in mediators based on a general planning
|
