ARKTOS: a knowledge engineering software tool for images

The goal of our ARKTOS project is to build an intelligent knowledge-based system to classify satellite sea ice images. It involves acquiring knowledge from sea ice experts, quantifying such knowledge as computational entities and ultimately building an intelligent classifier. In this paper we describe a two-stage knowledge engineering approach that facilitates explicit knowledge transfer, converting implicit visual cues and cognition of the experts to explicit attributes and rules implemented by the engineers. First, there is a prototyping stage that involves interviewing sea ice experts, transcribing the sessions, identifying descriptors and rules, designing and implementing the knowledge and delivering the prototype. The objective of this stage is to obtain a modestly accurate classification system quickly. Second, there is a refinement stage that involves evaluating the prototype, refining the knowledge base, modifying the design and re-evaluating the improved system. Since the refinement is evaluation-driven, the experts and the engineers are motivated explicitly to improve the knowledge base and are able to communicate with each other using a common, consistent platform. Moreover, since the classification result is immediately available, both sides are able to efficiently assess the correctness of the system. To facilitate the knowledge engineering of the second stage, we have designed and built three Java-based graphical user interfaces: arktosGUI, arktosViewer and arktosEditor. arktosGUI concentrates on feature-based refinement of specific attributes and rules. arktosViewer deals with regional evaluation. arktosEditor has a rule indexing and search mechanism and knowledge base editing capabilities. (C) 2002 Elsevier Science Ltd. All rights reserved

Tadzebao and WebOnto: discussing, browsing, and editing ontologies on the Web

In this paper I describe two systems which, in different ways, address the shortcomings of current approaches to enabling ontology construction and use via the World-Wide Web. The first system Tadzebao, enables knowledge engineers to hold synchronous and asynchronous discussions about ontologies. Tadzebao addresses the fact that an integral part of communal design, dialogue, has largely been ignored by the community. The second system WebOnto uses a Java based client to alleviate the acknowledged problems of creating interfaces in `vanilla HTML'

Using CommonKADS to Build an Expertise Model for Breast Cancer Prognosis and Therapy

One of the major aspects in breast cancer research is the identification of prognostic factors accurate enough to define different therapeutic decisions; each prognostic factor on its own is not sufficient for the prediction of the biological behaviour of the tumour, but a combination of these parameters is necessary. More over, nowadays growth of cancer literature, specifically on biological aspects, is of exponential nature, and the management of the knowledge deriving from cancer research needs a knowledge conceptualisation in order to semplify the process of guideline production in cancer prognosis and therapy. The work described here focuses on the definition of a conceptual knowledge model of the prognosis and the therapy of breast cancer. Our approach to the conceptualisation of the problem fol lows the CommonKADS (Knowledge Acquisition and Design Structuring) Library for Expertise Modelling. The aim of this work is to provide a first conceptual- isation of breast cancer prognosis and therapy, while evaluating the efficacy of the Com monKADS methodology in facing the problem

Framework para engenharia e processamento de ontologias utilizando computação quântica

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnoclógico, Programa de Pós-Graduação em Engenharia e Gestão do Conhecimento, Florianópolis, 2010Ontologias são recursos largamente utilizados para a representação de conhecimento em sistemas inteligentes. Ao longo do tempo, novos conhecimentos são adicionados e tais ontologias tendem a se tornar redes de complexidade crescente. Esta tese tem como objetivo trazer para a área da Engenharia Ontológica os benefícios de performance e representação que podem ser alcançados a partir do uso da Computação Quântica, a qual tem se mostrado vantajosa em áreas como a criptografia e buscas em conjuntos não ordenados. A abordagem é proposta a partir de um framework constituído dos seguintes conceitos derivados: superposição de classes, superposição de instâncias, superposição de relações e emaranhamento de classes. É demonstrado o uso de algoritmos quânticos para a superposição de classes e instâncias em ontologias, assim como aplicações sobre emaranhamento de classes. O trabalho também inclui um simulador para Computação Quântica como ferramenta de apoio na construção dos algoritmos, visualização dos circuitos quânticos e testes experimentais. A partir da ideia do armazenamento de estados superpostos por um tempo mais longo, o framework evolui para um modelo de representação de conhecimento em ontologias baseado no paradigma quântico. Sob esta ótica, são discutidas ramificações quanto à semelhança com o pensamento simbólico da mente humana e ainda o questionamento da própria definição de ontologias.Ontologies are resources widely used for representing knowledge in intelligent systems. Through the years, new knowledge has been added and such ontologies tend to become more and more complex networks. This paper is focused on the benefits of performance and representation for the Ontologies Engineering area, which can be obtained from the use of the Quantum Computing concepts. This fact has been considerely advantageous in certain science computing areas, such as encryption and searching in unordered sets. The approach is proposed through a framework that shows the following derived concepts: superposition of classes, entanglement of classes, superposition of instances and superposition of relations. It is demonstrated the use of quantum algorithms for superposition of instances and classes in ontologies, as well as some possible applications in entanglement of classes. The study also includes a Quantum Computing simulator as a helping tool in building algorithms, visualizing quantum circuits and experimental testing. From the idea of storing the quantum states in a superposition for longer periods of time, the framework evolves to a representation model based on the quantum paradigm. Under this perspective, there are some considerations over branches towards the similarity with the human mind symbolic way of thinking and even considerations on the proper concept of ontologies

On Formal Methods for Large-Scale Product Configuration

<p>In product development companies mass customization is widely used to achieve better customer satisfaction while keeping costs down. To efficiently implement mass customization, product platforms are often used. A product platform allows building a wide range of products from a set of predefined components. The process of matching these components to customers' needs is called product configuration. Not all components can be combined with each other due to restrictions of various kinds, for example, geometrical, marketing and legal reasons. Product design engineers develop configuration constraints to describe such restrictions. The number of constraints and the complexity of the relations between them are immense for complex product like a vehicle. Thus, it is both error-prone and time consuming to analyze, author and verify the constraints manually. Software tools based on formal methods can help engineers to avoid making errors when working with configuration constraints, thus design a correct product faster.</p> <p>This thesis introduces a number of formal methods to help engineers maintain, verify and analyze product configuration constraints. These methods provide automatic verification of constraints and computational support for analyzing and refactoring constraints. The methods also allow verifying the correctness of one specific type of constraints, item usage rules, for sets of mutually-exclusive required items, and automatic verification of equivalence of different formulations of the constraints. The thesis also introduces three methods for efficient enumeration of valid partial configurations, with benchmarking of the methods on an industrial dataset.</p> <p>Handling large-scale industrial product configuration problems demands high efficiency from the software methods. This thesis investigates a number of search-based and knowledge-compilation-based methods for working with large product configuration instances, including Boolean satisfiability solvers, binary decision diagrams and decomposable negation normal form. This thesis also proposes a novel method based on supervisory control theory for efficient reasoning about product configuration data. The methods were implemented in a tool, to investigate the applicability of the methods for handling large product configuration problems. It was found that search-based Boolean satisfiability solvers with incremental capabilities are well suited for industrial configuration problems.</p> <p>The methods proposed in this thesis exhibit good performance on practical configuration problems, and have a potential to be implemented in industry to support product design engineers in creating and maintaining configuration constraints, and speed up the development of product platforms and new products.</p

Multi-perspective modelling for knowledge management and knowledge engineering

ii It seems almost self-evident that “knowledge management ” and “knowledge engineering” should be related disciplines that may share techniques and methods between them. However, attempts by knowledge engineers to apply their techniques to knowledge management have been praised by some and derided by others, who claim that knowledge engineers have a fundamentally wrong concept of what “knowledge management” is. The critics also point to specific weaknesses of knowledge engineering, notably the lack of a broad context for the knowledge. Knowledge engineering has suffered some criticism from within its own ranks, too, particularly of the “rapid prototyping ” approach, in which acquired knowledge was encoded directly into an iteratively developed computer system. This approach was indeed rapid, but when used to deliver a final system, it became nearly impossible to verify and validate the system or to maintain it. A solution to this has come in the form of knowledge engineering methodology, and particularly in the CommonKAD