181,008 research outputs found
Introducing Dynamic Behavior in Amalgamated Knowledge Bases
The problem of integrating knowledge from multiple and heterogeneous sources
is a fundamental issue in current information systems. In order to cope with
this problem, the concept of mediator has been introduced as a software
component providing intermediate services, linking data resources and
application programs, and making transparent the heterogeneity of the
underlying systems. In designing a mediator architecture, we believe that an
important aspect is the definition of a formal framework by which one is able
to model integration according to a declarative style. To this purpose, the use
of a logical approach seems very promising. Another important aspect is the
ability to model both static integration aspects, concerning query execution,
and dynamic ones, concerning data updates and their propagation among the
various data sources. Unfortunately, as far as we know, no formal proposals for
logically modeling mediator architectures both from a static and dynamic point
of view have already been developed. In this paper, we extend the framework for
amalgamated knowledge bases, presented by Subrahmanian, to deal with dynamic
aspects. The language we propose is based on the Active U-Datalog language, and
extends it with annotated logic and amalgamation concepts. We model the sources
of information and the mediator (also called supervisor) as Active U-Datalog
deductive databases, thus modeling queries, transactions, and active rules,
interpreted according to the PARK semantics. By using active rules, the system
can efficiently perform update propagation among different databases. The
result is a logical environment, integrating active and deductive rules, to
perform queries and update propagation in an heterogeneous mediated framework.Comment: Other Keywords: Deductive databases; Heterogeneous databases; Active
rules; Update
Knowledge Representation Concepts for Automated SLA Management
Outsourcing of complex IT infrastructure to IT service providers has
increased substantially during the past years. IT service providers must be
able to fulfil their service-quality commitments based upon predefined Service
Level Agreements (SLAs) with the service customer. They need to manage, execute
and maintain thousands of SLAs for different customers and different types of
services, which needs new levels of flexibility and automation not available
with the current technology. The complexity of contractual logic in SLAs
requires new forms of knowledge representation to automatically draw inferences
and execute contractual agreements. A logic-based approach provides several
advantages including automated rule chaining allowing for compact knowledge
representation as well as flexibility to adapt to rapidly changing business
requirements. We suggest adequate logical formalisms for representation and
enforcement of SLA rules and describe a proof-of-concept implementation. The
article describes selected formalisms of the ContractLog KR and their adequacy
for automated SLA management and presents results of experiments to demonstrate
flexibility and scalability of the approach.Comment: Paschke, A. and Bichler, M.: Knowledge Representation Concepts for
Automated SLA Management, Int. Journal of Decision Support Systems (DSS),
submitted 19th March 200
Explaining Trained Neural Networks with Semantic Web Technologies: First Steps
The ever increasing prevalence of publicly available structured data on the
World Wide Web enables new applications in a variety of domains. In this paper,
we provide a conceptual approach that leverages such data in order to explain
the input-output behavior of trained artificial neural networks. We apply
existing Semantic Web technologies in order to provide an experimental proof of
concept
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