82,808 research outputs found
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
Logic Programming Approaches for Representing and Solving Constraint Satisfaction Problems: A Comparison
Many logic programming based approaches can be used to describe and solve
combinatorial search problems. On the one hand there is constraint logic
programming which computes a solution as an answer substitution to a query
containing the variables of the constraint satisfaction problem. On the other
hand there are systems based on stable model semantics, abductive systems, and
first order logic model generators which compute solutions as models of some
theory. This paper compares these different approaches from the point of view
of knowledge representation (how declarative are the programs) and from the
point of view of performance (how good are they at solving typical problems).Comment: 15 pages, 3 eps-figure
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Learning from AI : new trends in database technology
Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database
Using automated source code analysis for software evolution
Software maintenance is one of the most expensive and time-consuming phases in the software life-cycle. The size and complexity of commercial applications probably present the greatest difficulty that maintainers face when making changes to their applications. As a result of the corresponding loss of understanding, business knowledge encapsulated within the system becomes fragmented, and any changes made as a result of new business initiatives become difficult to implement and hence may mean a loss of business opportunities.
This paper outlines an approach to regaining understanding of software which has been used in the Release project at Durham University. This approach involves determining the calling structure of a program in terms of a call-graph, and from this call-graph extracting a dominance tree. Various problems which have been encountered during the construction of tools to perform this task are described
An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry
This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term
Second CLIPS Conference Proceedings, volume 1
Topics covered at the 2nd CLIPS Conference held at the Johnson Space Center, September 23-25, 1991 are given. Topics include rule groupings, fault detection using expert systems, decision making using expert systems, knowledge representation, computer aided design and debugging expert systems
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