Data are the lifeblood of an organisation, being employed by virtually all business functions within a firm. Data management, therefore, is a critical process in prolonging the life of a company and determining the success of each of an organisation’s business functions. The last decade and a half has seen data warehousing rising in priority within corporate data management as it provides an effective supporting platform for decision support tools. A cross-sectional survey conducted by this research showed that data warehousing is starting to be used within organisations for their engineering asset management, however the industry uptake is slow and has much room for development and improvement. This conclusion is also evidenced by the lack of systematic scholarly research within asset management data warehousing as compared to data warehousing for other business areas. This research is motivated by the lack of dedicated research into asset management data warehousing and attempts to provide original contributions to the area, focussing on data modelling. Integration is a fundamental characteristic of a data warehouse and facilitates the analysis of data from multiple sources. While several integration models exist for asset management, these only cover select areas of asset management. This research presents a novel conceptual data warehousing data model that integrates the numerous asset management data areas. The comprehensive ethnographic modelling methodology involved a diverse set of inputs (including data model patterns, standards, information system data models, and business process models) that described asset management data. Used as an integrated data source, the conceptual data model was verified by more than 20 experts in asset management and validated against four case studies. A large section of asset management data are stored in a relational format due to the maturity and pervasiveness of relational database management systems. Data warehousing offers the alternative approach of structuring data in a dimensional format, which suggests increased data retrieval speeds in addition to reducing analysis complexity for end users. To investigate the benefits of moving asset management data from a relational to multidimensional format, this research presents an innovative relational vs. multidimensional model evaluation procedure. To undertake an equitable comparison, the compared multidimensional are derived from an asset management relational model and as such, this research presents an original multidimensional modelling derivation methodology for asset management relational models. Multidimensional models were derived from the relational models in the asset management data exchange standard, MIMOSA OSA-EAI. The multidimensional and relational models were compared through a series of queries. It was discovered that multidimensional schemas reduced the data size and subsequently data insertion time, decreased the complexity of query conceptualisation, and improved the query execution performance across a range of query types. To facilitate the quicker uptake of these data warehouse multidimensional models within organisations, an alternate modelling methodology was investigated. This research presents an innovative approach of using a case-based reasoning methodology for data warehouse schema design. Using unique case representation and indexing techniques, the system also uses a business vocabulary repository to augment case searching and adaptation. The system was validated through a case-study where multidimensional schema design speed and accuracy was measured. It was found that the case-based reasoning system provided a marginal benefit, with a greater benefits gained when confronted with more difficult scenarios.

Zugl.: Osnabrück, Univ., Diss., 2006

Thesis (Ph.D.) - University of Queensland, 2005. / Includes bibliography.

Ces travaux concernent la mise en place d'un système d'aide à la décision, s'appuyant sur le raisonnement à partir de cas, pour la modélisation et la résolution des problèmes d'ordonnancement en génie des procédés. Une analyse de co-citation a été exécutée afin d'extraire de la littérature la connaissance nécessaire à la construction de la stratégie d'aide à la décision et d'obtenir une image de la situation, de l'évolution et de l'intensité de la recherche du domaine des problèmes d'ordonnancement. Un système de classification a été proposée, et la nomenclature proposée par Blazewicz et al. (2007) a été étendue de manière à pouvoir caractériser de manière complète les problèmes d'ordonnancement et leur mode de résolution. Les difficultés d'adaptation du modèle ont été discutées, et l'efficacité des quatre modèles de littérature a été comparée sur trois exemples de flow-shop. Une stratégie de résolution est proposée en fonction des caractéristiques du problème mathématique. / The purpose of this study is to work out the foundations of a decision-support system in order to advise efficient resolution strategies for scheduling problems in process engineering. This decision-support system is based on Case-Based Reasoning. A bibliographic study based on co-citation analysis has been performed in order to extract knowledge from the literature and obtain a landscape about scheduling research, its intensity and evolution. An open classification scheme has been proposed to scheduling problems, mathematical models and solving methods. A notation scheme corresponding to the classification has been elaborated based on the nomenclature proposed by Blazewicz et al. (2007). The difficulties arising during the adaptation of a mathematical model to different problems is discussed, and the performances of four literature mathematical models have been compared on three flow-shop examples. A resolution strategy is proposed based on the characteristics of the scheduling problem.

Raciocínio Baseado em Casos (RBC) a uma técnica de Inteligência Artificial para representação de conhecimento e inferência, que propõe a solução de novos problemas adaptando soluções que foram usadas para resolver problemas anteriores. A descrição de problemas existentes, conhecida como casos, é utilizada para sugerir um meio de resolver um novo problema, avisar o usuário de possíveis falhas observadas no passado e para interpretar a situação atual. Esta dissertação tem por objetivos apresentar um estudo sobre o use de RBC, aplicado ao desenvolvimento de um sistema de administração hospitalar. A aplicação escolhida é o controle e avaliação de Autorizações de Interações Hospitalares (AIH's). Atualmente, este controle é realizado manualmente pela Secretaria da Saúde Municipal de Porto Alegre, que tem um prazo de 48 horas para avaliar o faturamento de cada hospital e apontar as irregularidades. Isso é um problema, pois o volume do faturamento é grande para um prazo tão curto e muitas vezes as AIH's com irregularidades podem passar desapercebidas. O sistema considerado deve realizar o controle e avaliação de AIH's dos hospitais de Porto Alegre, e deve ser capaz de detectar irregularidades nãotriviais na cobrança das internações realizadas pelos hospitais conveniados do Sistema Único de Saúde (SUS). O estudo realizado considerou as etapas de aplicação da metodologia de RBC, tais como, a seleção de uma base de casos pré-existente, a aquisição de conhecimento para compreensão do processo de solução de problemas, a escolha da melhor estratégia de indexação de casos e a escolha do algoritmo de recuperação de casos. As etapas foram aplicadas cuidadosamente no desenvolvimento do protótipo dos métodos de controle de internações hospitalares realizadas pelo SUS e detalhadas para melhor compreensão de cada etapa. O texto ainda descreve a implementação do protótipo. Urna vantagem importante deste trabalho é que ele está vinculado ao projeto de Sistemas de Informação Distribuídos e Inteligentes — SIDI, que trata de Tecnologia de Modelagem, Projeto e Desenvolvimento de Sistemas de Bancos de Dados Distribuídos e Inteligente, no qual todo o estudo esta vinculado ao desenvolvimento de um grande sistema de informação inteligente e distribuído para controle de prontuários médicos de pacientes do Sistema Único de Saúde a nível de Municípios, para emissão de alertas e apoio a tomada de decisões na área de Saúde Pública também a nível de Municípios, e ainda para colocar a disposição da comunidade medica e administrativa abrangida pelo sistema um conjunto de documentos eletrônicos, com informações interessantes ou de referencia. Além de proporcionar uma revisão bibliográfica sobre sistemas de RBC e os vários sistemas já desenvolvidos, este trabalho mostra o desenvolvimento de um sistema de RBC para uma aplicação na área da saúde, detalhando cada uma de suas etapas e sua implementação, comparando as técnicas utilizadas em seu desenvolvimento com técnicas utilizadas em outros sistemas de RBC. / Case-based Reasoning (CBR) is an Artificial Intelligence (AI) technique for knowledge representation and inference that proposes the solution of new problems adapting old solutions used to solve previous problems. The problem description, cases, is used to suggest a way to solve a problem, get users attention to past failures current situation. The application which was chosen is the control and evaluation of Hospital Admission Authorization (AIH's). Actually, this control has been done by the Heath Bureau of Porto Alegre in 48 hours. They evaluate and point irregularities in the AIH's. That is a problem because the number of AIH's is large and the time is light and some of them can go uncovered. The present study must control and evaluate Porto Alegre AIH's and must be able to detect non trivial irregularities in hospital in admissions by the Health Unique System (SUS). The accomplished study considered the CBR methodology application stages, such as selection of a existent case base, the knowlegde acquisition process to understand the solution process, the case representation, choice of the best indexing scheme and the recovery algorithm. The stages were carefully applied in the control methods prototype development of hospital admissions by the SUS. The text describes yet the prototype implementation. An important advantage of this work is that it is related to the SIDI (Inteligent and Distributed Information System) project. This project focuses on the Modelling, Project and Development of a Distributed and Intelligent Database System, in which the work being done aims at the development of a great information system to control dossier of pacients, to emit alerts, to help municipals district in decision support, and to give doctors the chance to have important eletronic documents to search. Besides presenting a survey about CBR systems and previous systems developed, this work shows the development of a CBR system to medical computer science, presenting each stage of the system and its implementation, comparing the techniques used here with those used in the others systems.

Case-Based Reasoning (CBR) is an Artificial Intelligence (AI) methodology and a growing field of research. CBR uses past experiences to help solve new problems the system faces. To do so CBR is comprised of a few core parts, such as case representation, case library, case retrieval, and case adaptation. This thesis will focus on the case representation aspect of CBR systems and presents a scalable case representation for big data environments. One aspect of focus on big data environments is also the focus of a MapReduce environment. MapReduce is a software framework enabling the use of a Map and Reduce function to be executed over a network cluster. This thesis conducts a systematic literature review to gain an understanding of the current case representations used in various CBR systems. The systematic literature review presents two major types of case representations, hierarchical and vector-based representations. However, the review also finds that the field of case representation research to be lacking. Most papers were focused on other aspects of CBR systems, mainly case retrieval. This thesis also proposes the design of a scalable and distributed case representation. The proposed case representation is of a hierarchical nature and is designed in such a way that it can utilize a MapReduce environment for working with the case library in components such as case retrieval. In the proof of concept, part of the case representation was implemented and tested using two data-sets. One data-set contains EEG sensor data measuring sleepiness while the other contains information about employees health and time taken off work. These tests show the case representation adequately representing the respective data-sets. The strength of the proposed case representation method is further discussed using a cross of papers. These papers cover the use of XML structured data in both CBR and MapReduce showing how this case representation is suitable for both uses. This shows strong capabilities of the case representation being further implemented and the addition of a case retrieval method to utilize it.

Raciocínio Baseado em Casos (RBC) a uma técnica de Inteligência Artificial para representação de conhecimento e inferência, que propõe a solução de novos problemas adaptando soluções que foram usadas para resolver problemas anteriores. A descrição de problemas existentes, conhecida como casos, é utilizada para sugerir um meio de resolver um novo problema, avisar o usuário de possíveis falhas observadas no passado e para interpretar a situação atual. Esta dissertação tem por objetivos apresentar um estudo sobre o use de RBC, aplicado ao desenvolvimento de um sistema de administração hospitalar. A aplicação escolhida é o controle e avaliação de Autorizações de Interações Hospitalares (AIH's). Atualmente, este controle é realizado manualmente pela Secretaria da Saúde Municipal de Porto Alegre, que tem um prazo de 48 horas para avaliar o faturamento de cada hospital e apontar as irregularidades. Isso é um problema, pois o volume do faturamento é grande para um prazo tão curto e muitas vezes as AIH's com irregularidades podem passar desapercebidas. O sistema considerado deve realizar o controle e avaliação de AIH's dos hospitais de Porto Alegre, e deve ser capaz de detectar irregularidades nãotriviais na cobrança das internações realizadas pelos hospitais conveniados do Sistema Único de Saúde (SUS). O estudo realizado considerou as etapas de aplicação da metodologia de RBC, tais como, a seleção de uma base de casos pré-existente, a aquisição de conhecimento para compreensão do processo de solução de problemas, a escolha da melhor estratégia de indexação de casos e a escolha do algoritmo de recuperação de casos. As etapas foram aplicadas cuidadosamente no desenvolvimento do protótipo dos métodos de controle de internações hospitalares realizadas pelo SUS e detalhadas para melhor compreensão de cada etapa. O texto ainda descreve a implementação do protótipo. Urna vantagem importante deste trabalho é que ele está vinculado ao projeto de Sistemas de Informação Distribuídos e Inteligentes — SIDI, que trata de Tecnologia de Modelagem, Projeto e Desenvolvimento de Sistemas de Bancos de Dados Distribuídos e Inteligente, no qual todo o estudo esta vinculado ao desenvolvimento de um grande sistema de informação inteligente e distribuído para controle de prontuários médicos de pacientes do Sistema Único de Saúde a nível de Municípios, para emissão de alertas e apoio a tomada de decisões na área de Saúde Pública também a nível de Municípios, e ainda para colocar a disposição da comunidade medica e administrativa abrangida pelo sistema um conjunto de documentos eletrônicos, com informações interessantes ou de referencia. Além de proporcionar uma revisão bibliográfica sobre sistemas de RBC e os vários sistemas já desenvolvidos, este trabalho mostra o desenvolvimento de um sistema de RBC para uma aplicação na área da saúde, detalhando cada uma de suas etapas e sua implementação, comparando as técnicas utilizadas em seu desenvolvimento com técnicas utilizadas em outros sistemas de RBC. / Case-based Reasoning (CBR) is an Artificial Intelligence (AI) technique for knowledge representation and inference that proposes the solution of new problems adapting old solutions used to solve previous problems. The problem description, cases, is used to suggest a way to solve a problem, get users attention to past failures current situation. The application which was chosen is the control and evaluation of Hospital Admission Authorization (AIH's). Actually, this control has been done by the Heath Bureau of Porto Alegre in 48 hours. They evaluate and point irregularities in the AIH's. That is a problem because the number of AIH's is large and the time is light and some of them can go uncovered. The present study must control and evaluate Porto Alegre AIH's and must be able to detect non trivial irregularities in hospital in admissions by the Health Unique System (SUS). The accomplished study considered the CBR methodology application stages, such as selection of a existent case base, the knowlegde acquisition process to understand the solution process, the case representation, choice of the best indexing scheme and the recovery algorithm. The stages were carefully applied in the control methods prototype development of hospital admissions by the SUS. The text describes yet the prototype implementation. An important advantage of this work is that it is related to the SIDI (Inteligent and Distributed Information System) project. This project focuses on the Modelling, Project and Development of a Distributed and Intelligent Database System, in which the work being done aims at the development of a great information system to control dossier of pacients, to emit alerts, to help municipals district in decision support, and to give doctors the chance to have important eletronic documents to search. Besides presenting a survey about CBR systems and previous systems developed, this work shows the development of a CBR system to medical computer science, presenting each stage of the system and its implementation, comparing the techniques used here with those used in the others systems.

Raciocínio Baseado em Casos (RBC) a uma técnica de Inteligência Artificial para representação de conhecimento e inferência, que propõe a solução de novos problemas adaptando soluções que foram usadas para resolver problemas anteriores. A descrição de problemas existentes, conhecida como casos, é utilizada para sugerir um meio de resolver um novo problema, avisar o usuário de possíveis falhas observadas no passado e para interpretar a situação atual. Esta dissertação tem por objetivos apresentar um estudo sobre o use de RBC, aplicado ao desenvolvimento de um sistema de administração hospitalar. A aplicação escolhida é o controle e avaliação de Autorizações de Interações Hospitalares (AIH's). Atualmente, este controle é realizado manualmente pela Secretaria da Saúde Municipal de Porto Alegre, que tem um prazo de 48 horas para avaliar o faturamento de cada hospital e apontar as irregularidades. Isso é um problema, pois o volume do faturamento é grande para um prazo tão curto e muitas vezes as AIH's com irregularidades podem passar desapercebidas. O sistema considerado deve realizar o controle e avaliação de AIH's dos hospitais de Porto Alegre, e deve ser capaz de detectar irregularidades nãotriviais na cobrança das internações realizadas pelos hospitais conveniados do Sistema Único de Saúde (SUS). O estudo realizado considerou as etapas de aplicação da metodologia de RBC, tais como, a seleção de uma base de casos pré-existente, a aquisição de conhecimento para compreensão do processo de solução de problemas, a escolha da melhor estratégia de indexação de casos e a escolha do algoritmo de recuperação de casos. As etapas foram aplicadas cuidadosamente no desenvolvimento do protótipo dos métodos de controle de internações hospitalares realizadas pelo SUS e detalhadas para melhor compreensão de cada etapa. O texto ainda descreve a implementação do protótipo. Urna vantagem importante deste trabalho é que ele está vinculado ao projeto de Sistemas de Informação Distribuídos e Inteligentes — SIDI, que trata de Tecnologia de Modelagem, Projeto e Desenvolvimento de Sistemas de Bancos de Dados Distribuídos e Inteligente, no qual todo o estudo esta vinculado ao desenvolvimento de um grande sistema de informação inteligente e distribuído para controle de prontuários médicos de pacientes do Sistema Único de Saúde a nível de Municípios, para emissão de alertas e apoio a tomada de decisões na área de Saúde Pública também a nível de Municípios, e ainda para colocar a disposição da comunidade medica e administrativa abrangida pelo sistema um conjunto de documentos eletrônicos, com informações interessantes ou de referencia. Além de proporcionar uma revisão bibliográfica sobre sistemas de RBC e os vários sistemas já desenvolvidos, este trabalho mostra o desenvolvimento de um sistema de RBC para uma aplicação na área da saúde, detalhando cada uma de suas etapas e sua implementação, comparando as técnicas utilizadas em seu desenvolvimento com técnicas utilizadas em outros sistemas de RBC. / Case-based Reasoning (CBR) is an Artificial Intelligence (AI) technique for knowledge representation and inference that proposes the solution of new problems adapting old solutions used to solve previous problems. The problem description, cases, is used to suggest a way to solve a problem, get users attention to past failures current situation. The application which was chosen is the control and evaluation of Hospital Admission Authorization (AIH's). Actually, this control has been done by the Heath Bureau of Porto Alegre in 48 hours. They evaluate and point irregularities in the AIH's. That is a problem because the number of AIH's is large and the time is light and some of them can go uncovered. The present study must control and evaluate Porto Alegre AIH's and must be able to detect non trivial irregularities in hospital in admissions by the Health Unique System (SUS). The accomplished study considered the CBR methodology application stages, such as selection of a existent case base, the knowlegde acquisition process to understand the solution process, the case representation, choice of the best indexing scheme and the recovery algorithm. The stages were carefully applied in the control methods prototype development of hospital admissions by the SUS. The text describes yet the prototype implementation. An important advantage of this work is that it is related to the SIDI (Inteligent and Distributed Information System) project. This project focuses on the Modelling, Project and Development of a Distributed and Intelligent Database System, in which the work being done aims at the development of a great information system to control dossier of pacients, to emit alerts, to help municipals district in decision support, and to give doctors the chance to have important eletronic documents to search. Besides presenting a survey about CBR systems and previous systems developed, this work shows the development of a CBR system to medical computer science, presenting each stage of the system and its implementation, comparing the techniques used here with those used in the others systems.

In order for an agent to be considered both an interface agent and autonomous, it follows that there must be some part of the interface that the agent must operate in an autonomous fashion. The user must be able to directly observe autonomous actions of the agent and the agent must be able to observe actions taken autonomously by the user in the interface The ability of a software agent to operate the same interface operated by the human user, and the ability of a software agent to act independently of, and concurrently with, the human user will become increasingly important characteristics of human-computer interaction. Agents will observe what human users do when they interact with interfaces, and provide assistance by manipulating the interface themselves, while the user is thinking or performing other operations. Increasingly, applications will be designed to be operated simultaneously by users and their agents [1]. This study is motivated by the need to solve a problem of human resource optimization in the first year informatics practical course as presented by the R.A.U. Standard Bank Academy for Information Technology. The major aim being the development of a prototype system capable of automatically grading first year Microsoft Visual Basic.Net applications. The prototype system will ultimately render assistants obsolete in the grading process and free the assistants to help students with problems related to the informatics course. Developing the envisaged prototype requires much preliminary reading on artificial intelligence and its applications, more specifically autonomous interface agent architecture. Case-based reasoning and machine learning has been identified as having great potential and applicability in the development and implementation of the envisaged prototype and for this reason these topics will provide a foundation on which to build this dissertation. / Ehlers, E.M., Prof.

Context: Software effort estimation is a very important component of the software development life cycle. It underpins activities such as planning, maintenance and bidding. Therefore, it has triggered much research over the past four decades, including many machine learning approaches. One popular approach, that has the benefit of accessible reasoning, is analogy-based estimation. Machine learning including analogy is known to significantly benefit from feature selection/weighting. Unfortunately feature weighting search is an NP hard problem, therefore computationally very demanding, if not intractable. Objective: Therefore, one objective of this research is to develop an effi cient and effective feature weighting algorithm for estimation by analogy. However, a major challenge for the effort estimation research community is that experimental results tend to be contradictory and also lack reliability. This has been paralleled by a recent awareness of how bias can impact research results. This is a contributory reason why software effort estimation is still an open problem. Consequently the second objective is to investigate research methods that might lead to more reliable results and focus on blinding methods to reduce researcher bias. Method: In order to build on the most promising feature weighting algorithms I conduct a systematic literature review. From this I develop a novel and e fficient feature weighting algorithm. This is experimentally evaluated, comparing three feature weighting approaches with a na ive benchmark using 2 industrial data sets. Using these experiments, I explore blind analysis as a technique to reduce bias. Results: The systematic literature review conducted identified 19 relevant primary studies. Results from the meta-analysis of selected studies using a one-sample sign test (p = 0.0003) shows a positive effect - to feature weighting in general compared with ordinary analogy-based estimation (ABE), that is, feature weighting is a worthwhile technique to improve ABE. Nevertheless the results remain imperfect so there is still much scope for improvement. My experience shows that blinding can be a relatively straightforward procedure. I also highlight various statistical analysis decisions which ought not be guided by the hunt for statistical significance and show that results can be inverted merely through a seemingly inconsequential statistical nicety. After analysing results from 483 software projects from two separate industrial data sets, I conclude that the proposed technique improves accuracy over the standard feature subset selection (FSS) and traditional case-based reasoning (CBR) when using pseudo time-series validation. Interestingly, there is no strong evidence for superior performance of the new technique when traditional validation techniques (jackknifing) are used but is more effi cient. Conclusion: There are two main findings: (i) Feature weighting techniques are promising for software effort estimation but they need to be tailored for target case for their potential to be adequately exploited. Despite the research findings showing that assuming weights differ in different parts of the instance space ('local' regions) may improve effort estimation results - majority of studies in software effort estimation (SEE) do not take this into consideration. This represents an improvement on other methods that do not take this into consideration. (ii) Whilst there are minor challenges and some limits to the degree of blinding possible, blind analysis is a very practical and an easy-to-implement method that supports more objective analysis of experimental results. Therefore I argue that blind analysis should be the norm for analysing software engineering experiments.