Journal ArticleDOI
Retrieving and Integrating Data from Multiple Information Sources
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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.Abstract:
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.read more
Citations
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Book
The Description Logic Handbook
TL;DR: This introduction presents the main motivations for the development of Description Logics as a formalism for representing knowledge, as well as some important basic notions underlying all systems that have been created in the DL tradition.
Journal ArticleDOI
What are ontologies, and why do we need them?
TL;DR: A conceptual introduction to ontologies and their role in information systems and AI is provided and how ontologies clarify the domain's structure of knowledge and enable knowledge sharing is discussed.
Proceedings Article
Ontology-Based Integration of Information — A Survey of Existing Approaches
Holger Wache,Thomas Vögele,Ubbo Visser,Heiner Stuckenschmidt,Gerhard Schuster,Heiko Neumann,Sebastian Hübner +6 more
TL;DR: The state of the art in ontology-based information integration is summarized and the use on ontologies for the integration of heterogeneous information sources is reviewed.
Proceedings Article
Querying Heterogeneous Information Sources Using Source Descriptions
TL;DR: The Information Manifold is described, an implemented system that provides uniform access to a heterogeneous collection of more than 100 information sources, many of them on the WWW, and algorithms that use the source descriptions to prune effciently the set of information sources for a given query are described.
Journal ArticleDOI
The TSIMMIS Approach to Mediation: Data Models and Languages
Hector Garcia-Molina,Yannis Papakonstantinou,Dallan Quass,Anand Rajaraman,Yehoshua Sagiv,Jeffrey D. Ullman,Vasilis Vassalos,Jennifer Widom +7 more
TL;DR: TSIMMIS—The Stanford-IBM Manager of Multiple Information sources offers a datamodel and a common query language that are designed to support the combining of information from many different sources.
References
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Book ChapterDOI
Rete: a fast algorithm for the many pattern/many object pattern match problem
TL;DR: The Rete Match Algorithm is an efficient method for companng a large collection of patterns to a largeCollection of objects that finds all the objects that match each pattern.
Book
Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project
TL;DR: This review has been difficult for me to write, because my thoughts about Cyc have changed a great deal since I first read the book in the spring of 1990 and I agree with his complaints about the confusing organization of the book and the lack of precise definitions.
Journal ArticleDOI
A theory and methodology of inductive learning
TL;DR: The authors view inductive learning as a heuristic search through a space of symbolic descriptions, generated by an application of various inference rules to the initial observational statements, including generalization rules, which perform generalizing transformations on descriptions, and conventional truth-preserving deductive rules.
Journal ArticleDOI
Semantic database modeling: survey, applications, and research issues
Richard Hull,Roger King +1 more
TL;DR: This paper provides a tutorial introduction to the primary components of semantic models, which are the explicit representation of objects, attributes of and relationships among objects, type constructors for building complex types, ISA relationships, and derived schema components.
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