依財政部保險司每半年對壽險申訴案件的統計觀察，客戶對壽險公司提出申訴的件數有逐年遞增的趨勢，申訴原因多為理賠給付、契約保全服務、業務員招攬、保費收費糾紛、商品條款及法規等爭議。客服員若能於第一時間以專業的知識回應申訴問題，勢必可減少申訴數量。但面對浩瀚的壽險各領域知識，客服中心的成員不易具備所有足以應付客戶問題的知識，實施知識管理將組織內各種知識公開化、標準化、制度化、科技化，已成為刻不容緩的任務。 為解決壽險客服中心因取得壽險專業知識的障礙而無法提供客戶滿意的服務，本研究對客服中心可能應用的各種知識，探討已被發表的知識管理分類、呈現與檢索等應用的相關技術，提出符合客服中心需求的以知識本體為基礎的壽險知識問題檢索架構，除了提供壽險專業知識的建立、搜尋、分享環境，並將原始文件儲存為XML或RDF的語意文件，做為將來跨平台與跨應用系統資料交換的基礎，提升客服中心服務效率、節省客服人力與行政成本，留住忠誠的客戶以達成CRM的目的，進而提升企業競爭力。 / According to the regular semi-annual statistic report from Insurance Department of MOF Taiwan, the complain cases from policy owners are increasing year by year. The reasons of complain are claims, underwriting, policy services, marketing, premium collections, policy clauses and regulations. If the customer service representatives (CSR) could solve the problems at the right time with their domain knowledge of life insurance, the volumes of complain should be descended explicitly. But it is hard to ask a CSR to play the role with variety domain knowledge of life insurance. Implement the knowledge management mechanism to standardize and enrich the organization memory are the first priority in life insurance companies. In order to overcome the barrier of dissatisfaction about customer service, this research try to study the related theories and technologies of knowledge classification, knowledge representation, knowledge acquisition tools, inference and problem solving methods. The results of this research announce an architecture of ontology based customer relationship management for Life Insurance Company to build, represent, search, and share the life insurance domain knowledge. Addition, to save the original semi-structured or unstructured documents into semantic formats of XML or RDF. It could provides the data exchange between heterogeneous databases and platforms. The advantages are more efficiency and cost down for the customer service departments, retain the royalty customers and get more competence advantage for the company.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal.

Nous cherchons dans cette étude à développer des compétences de la pensée critique et créative et l’acquisition de connaissances chez un groupe d’élèves dans des écoles de collégiens en Syrie, à travers l'application de la méthode Freinet dans le processus d'apprentissage. Pour valider des hypothèses de la recherche, nous avons enseigné à deux groupes d’élèves – contrôle et expérimental – une unité de la matière de sciences S.V.T par deux styles. Le premier groupe a été enseigné par le style traditionnel (groupe contrôle), le deuxième a été enseigné par la méthode de Freinet . Pour mesurer le développement des compétences de la pensée critique et créative chez les élèves, nous avons conçu deux tests ; le premier, pour mesurer les compétences principales de la pensée critique et le deuxième, pour mesurer les compétences principales de la pensée créative. Afin de mesurer le développement du niveau d’acquisition des connaissances chez les élèves, nous avons conçu un test traditionnel à propos des informations contenues dans l’unité éducative au manuel de sciences S.V.T. Les résultats de cette étude ont montré l'efficacité de cette méthode dans le développement de cinq compétences principales de la pensée critique chez les élèves. L'étude a également montré l'efficacité de cette méthode dans le développement de trois compétences principales de la pensée créative chez les élèves. En plus, les résultats de cette étude ont montré que l’enseignement par la méthode de Freinet a contribué au développement du niveau d’acquisition des connaissances chez les élèves. / Through this research, we are looking to develop Critical Thinking Skills and Creative Thinking Skills, as well as the acquisition of knowledge in a group of students in college schools in Syria, through the application of the Freinet method in the learning process. To validate the hypothesis of the research, we taught two groups – control & experimental – of students a unit of a science S.V.T. manual. Two styles were used: the first group was taught by the traditional method (control group), the second taught by the method of Freinet (experimental group). To measure the development of the Critical Thinking Skills and the Creative Thinking Skills in students, we designed two tests: the first, to measure the Critical Thinking Skills, and the second, to measure the Creative Thinking Skills. To measure the development of the students' level of knowledge acquisition, we designed a traditional test about the information contained in the educational unit in the S.V.T. book. The results of this study showed the effectiveness of this method in developing five skills of the critical thinking in students (inference, assumption, deduction, interpretation, and evaluation of the argument). The study also showed the effectiveness of this method in developing three skills of the creative thinking in students (originality, fluidity, and flexibility). In addition, the results of this study showed that the teaching by the Freinet method has contributed to the development of students' level of knowledge acquisition.

Os avanços tecnológicos da última década tem feito dos computadores um elemento de contribuição essencial para os processos de solução de problemas e de tomada de decisão cooperativos. Hoje, alem do interesse mantido nos sistemas de solução de problemas, cujo raciocínio a baseado no processo de decisão de um único individuo (conhecidos por SE's), o esforço das pesquisas, em Inteligência Artificial, esta centrado no sentido de conceber sistemas que permitam a interação cooperativa entre diversos indivíduos participantes do processo, sejam esses humanos ou sistemas computacionais. A solução de problemas cooperativos, dentro do escopo geral da Inteligência Artificial (IA), é assunto analisado sob dois aspectos diferentes. O primeiro, mais antigo, identifica, como agentes de um dialogo, o sistema computacional e o seu usuário, onde pesquisas estão centradas no estudo da interação homem-máquina. Os esforços desta área de pesquisa tem sido no sentido de conceber, aos sistemas, capacidades de comunicação muito mais ricas do que aquelas oferecidas por sistemas de solução de problemas tradicionais, isto é, permitir aos sistemas compartilhar a solução de um problema, tomando o usuário um agente muito mais ativo e participativo. O segundo aspecto situa-se na área de Inteligência Artificial Distribuída (IAD), uma nova concepção de IA que acompanha o avanço da tecnologia de desenvolvimento de maquinas paralelas e a difusão, em larga escala, de sistemas computacionais distribuídos. Seus esforços são no sentido de conceber sistemas compostos de múltiplos sub-sistemas, capazes de resolver problemas complexos autonomamente. de forma cooperativa. Este trabalho se insere no contexto da interação homem-máquina. São apresentados métodos e estratégias para o fornecimento de capacidades cooperativas ao sistema. A descrição de uma arquitetura para Sistemas Especialistas (SE), baseada em raciocínio meta-nível, é apresentada com o intuito de enriquecer as capacidades de explanação e aquisição de conhecimentos desses sistemas. Consideramos que as ferramentas de explanação e aquisição de conhecimentos são fundamentais para a construção de diálogos cooperativos entre o sistema e o usuário. A ferramenta de explanação é o componente do SE responsável pela geração de justificativas sobre as conclusões do sistema. Ela permite ao sistema tornar explicito o seu raciocínio, fornecendo capacidades de argumentação sobre a validade de suas conclusões. O sistema, através desta ferramenta, tem condições de explicar suas ações, conclusões. escolhas e perguntas feitas ao usuário, permitindo, dessa forma, ao próprio usuário. através de um diálogo cooperativo. comparar seus conhecimentos e estratégias. concordando ou discordando do sistema. A ferramenta de aquisição de conhecimento. outro modulo importante num processo cooperativo, permite ao sistema aprender incrementalmente, através da aquisição de novos conhecimentos, bem como da reestruturação de alguns conhecimentos ou regras com falhas. Analisa-se um problema real, cuja solução e concebida através da interação homem-máquina. embora, intuitivamente, seja apresentada uma abordagem multi-agente para o problema, no final deste trabalho, com o intuito de apontar a evolução que terá essa pesquisa. Como produto deste trabalho de pesquisa, desenvolveu-se, dentro do projeto Inteligência Artificial Distribuída do grupo de Inteligência Artificial do CPGCC da UFRGS. urn sistema denominado SETA. O sistema permite a criação de SE's dedicados a auxiliar o medico na prescrição farmacológica de qualquer grupo de patologia clinica. A representação do conhecimento aplicado foi desenvolvida com o intuito de facilitar a atividade de formulação de prescrições onde o conhecimento esta estruturado em níveis de representação que denotam os conhecimentos clínico e farmacológico separadamente. Cada SE, desenvolvido pelo SETA, permite oferecer justificativas claras ao usuário sobre a prescrição farmacológica indicada pelo sistema, através de explanações do tipo how. why e why not. Oferece, ainda, facilidades de aquisição de conhecimento, permitindo a modificação do conhecimento do sistema através de um modulo interativo, cuja interface foi construída no sentido de permitir uma comunicacc7o natural entre os agentes. ou seja. o sistema e o medico especialista. Resumindo, a interação cooperativa homem-máquina é concebida através das facilidades de explanação e aquisição de conhecimento, levando a incorporação explicita de meta-conhecimento ao sistema. / The technological advance of the past decade turned computers into an element of essential contribution for the cooperative problem-solving and decision-taking processes. Today, besides the interest kept in problem-solving systems, whose reasoning is based upon the process of decision of a single individual (known as ES), the effort of researchs in Artificial Intelligence is to create systems that allow cooperative interaction among various individuals participating in the process, these being either human beings or computer systems. The solution of cooperative problems, within the general scope of Artificial Intelligence, is a subject analysed under two different aspects. The first one, out of date, identifies the computer system and its user as agents in a dialogue, and the researches are concentrated on the study of man-machine interaction. The efforts in this area of research have been to grant the systems communication abilities much richer than those offered by tradicional problem-solving systems. that is, that allow the systems to share the solution of a problem. causing the user to be more active and participating. The second aspect is located in the area of Distributed Artificial Intelligence (DAI), a new conception of AI that goes with the improvement of the technology of development of parallel machines and the diffusion on a large scale of distributed computer systems. Efforts have been made to create systems made up of multiple sub-systems capable of solving complex problems by themselves, in a cooperative way. This work is inserted in the context of man-machine interaction. It presents methods and strategies to supply the system with cooperative abilities. The description of an architecture for Expert Systems (ES), based upon meta-level reasoning, is presented with the purpose of improving the abilities of explanation and knowledge acquisition of these systems. We consider explanation tools and knowledge acquisition to be fundamental to the construction of cooperative dialogues between the system and the user. The explanation tool is the ES component responsible for the generation of justifications about the system conclusions. It allows the system to make its reasoning explicit, providing it with arguing abilities about the effectiveness of its conclusions. The system. through this tool, is able to explain its actions, conclusions, choices and questions put to the user, thus allowing the user, through a cooperative dialogue, to compare his knowledge and strategies, to agree or disagree with the system. The knowledge acquisition tool, another important unit in a cooperative process, allows the system to learn more and more through the acquisition of new knowledge as well as through the restructuration of knowledge or rules that have failed. A real problem is analysed here and its solution is conceived through manmachine interaction. We also present, at the end of this work, a multi-agent approach for the problem, in order to show how this research will evolve. This research work resulted in the development, within the Distributed Artificial Intelligence project of the Artificial Intelligence group of the CPGCC of UFRGS, of a system called SETA. This system permits the creation of ES dedicated to help doctors prescribe medicines for any groups of clinical pathology. The knowledge representation used was developed with a view to facilitate the making of prescriptions, and the knowledge is organized in levels of representation that express clinical knowledge and pharmacological knowledge separately. Each ES developed by SETA can offer reasonable justifications to users about the pharmacological prescription indicated by the system through explanations such as how, why and why not. It is also ready to acquire knowledge. allowing the system to alter knowledge through an interactive unit whose interface was built to permit a natural communication between the agents. that is, the system and the medical specialist. In short, man-machine cooperative interaction is based upon readiness for explanation and knowledge acquisition, leading to an explicit assimilation of meta-knowledge by the system.

Com a popularização de ferramentas computacionais aplicadas ao ensino e o advento da Web 2.0, os Ambientes Virtuais de Aprendizagem (AVAs) evoluíram com os recursos proporcionados pelas tecnologias de Realidade Virtual (RV) e Realidade Aumentada (RA), surgindo os AVAs tridimensionais (3D), amplamente adotados em diversos domínios de conhecimento. Aliado a este avanço, o processo de aquisição de conhecimento em AVAs 3D tem sido alvo de pesquisas a fim de que tal aspecto seja considerado na concepção dos ambientes virtuais. Uma discussão que é delineada neste contexto se refere à contribuição que os AVAs 3D efetivamente oferecem para a aquisição de conhecimento do aprendiz e como é possível avaliar tal aprendizado. Estudos têm demonstrado que os métodos amplamente aplicados para avaliação da cognição nos AVAs 3D têm feito uso intensivo de preenchimento de questionários, aplicados fora dos AVAs. É possível perceber ainda que os instrumentos de avaliação aplicados nos AVAs 3D não incorporam no processo de avaliação as próprias tecnologias interativas disponíveis no ambiente. Sendo assim, o propósito inicial desta pesquisa é identificar o processo de aquisição de conhecimento nos AVAs 3D, como também os métodos existentes para avaliar se ocorre de fato a aquisição de conhecimento e em que grau ela ocorre. A partir deste estudo, o objetivo deste trabalho é definir uma metodologia para avaliar a aquisição de conhecimento, usando as próprias tecnologias interativas disponíveis nos AVAs 3D, de forma inovadora, em complementação aos questionários amplamente empregados como instrumentos de avaliação. Além da proposição do método conceitual, foi definida uma arquitetura e implementado um sistema computacional capaz de registrar as interações dos usuários em AVAs 3D, de forma não intrusiva à aplicação. Também foi sugerido um modelo matemático que propõe a avaliação da aprendizagem sem a necessidade de execução de provas de conhecimento. Experimentos foram conduzidos para avaliar cada uma das fases do modelo. Os resultados dos experimentos mostraram que é factível avaliar a aquisição de conhecimento dentro de contextos pré-determinados e que há indícios de que alguns tipos de interações do usuário com os AVAs mantêm correlação com o nível de aprendizado do usuário. / The popularization of computational tools applied to teaching and the advent of Web 2.0 have led to the advancement of Virtual Learning Environments (VLE) through resources rendered by Virtual Reality (VR) and Augmented Reality (AR) technologies, leading to the emergence of Tridimensional VLEs (3D), which are widely employed in diverse fields of knowledge. In alliance with this advancement, the 3D VLE knowledge acquisition process has been the object of research studies which consider the conception of virtual environments. One of the discussions outlined in this context refers to the contribution that 3D VLEs effectively offer for knowledge acquisition and how it is possible to evaluate this learning process. Studies have demonstrated that methods widely employed for assessing cognition in 3D VLEs have made intense use of questionnaire application outside VLEs. It is possible to perceive that, in the evaluation process, the assessment tools applied in 3D VLEs do not incorporate the same interactive technologies available in the environment. Thus, the initial aim of this research is to identify the knowledge acquisition process in 3D VLEs, as well as existing methods for assessing if knowledge acquisition actually occurs and to which degree it occurs. From this study, the aim of the research is to define a method for assessing knowledge acquisition employing the same interactive technologies available in 3D VLEs, in an innovative manner, complementing widely used questionnaires as assessment tools. In addition to the suggestion of the conceptual method, an architecture was defined and a computational system capable of registering user interactions in 3D VLEs was implemented, in a non intrusive form of application. A mathematical model that offers learning assessment without the need of knowledge tests was also suggested. Experiments were conducted to evaluate each phase of the model. The results of the experiments show that it is feasible to evaluate knowledge acquisition within predetermined contexts and that there is evidence that some types of user interactions with VLEs are correlated with the user\'s learning level.

Com a popularização de ferramentas computacionais aplicadas ao ensino e o advento da Web 2.0, os Ambientes Virtuais de Aprendizagem (AVAs) evoluíram com os recursos proporcionados pelas tecnologias de Realidade Virtual (RV) e Realidade Aumentada (RA), surgindo os AVAs tridimensionais (3D), amplamente adotados em diversos domínios de conhecimento. Aliado a este avanço, o processo de aquisição de conhecimento em AVAs 3D tem sido alvo de pesquisas a fim de que tal aspecto seja considerado na concepção dos ambientes virtuais. Uma discussão que é delineada neste contexto se refere à contribuição que os AVAs 3D efetivamente oferecem para a aquisição de conhecimento do aprendiz e como é possível avaliar tal aprendizado. Estudos têm demonstrado que os métodos amplamente aplicados para avaliação da cognição nos AVAs 3D têm feito uso intensivo de preenchimento de questionários, aplicados fora dos AVAs. É possível perceber ainda que os instrumentos de avaliação aplicados nos AVAs 3D não incorporam no processo de avaliação as próprias tecnologias interativas disponíveis no ambiente. Sendo assim, o propósito inicial desta pesquisa é identificar o processo de aquisição de conhecimento nos AVAs 3D, como também os métodos existentes para avaliar se ocorre de fato a aquisição de conhecimento e em que grau ela ocorre. A partir deste estudo, o objetivo deste trabalho é definir uma metodologia para avaliar a aquisição de conhecimento, usando as próprias tecnologias interativas disponíveis nos AVAs 3D, de forma inovadora, em complementação aos questionários amplamente empregados como instrumentos de avaliação. Além da proposição do método conceitual, foi definida uma arquitetura e implementado um sistema computacional capaz de registrar as interações dos usuários em AVAs 3D, de forma não intrusiva à aplicação. Também foi sugerido um modelo matemático que propõe a avaliação da aprendizagem sem a necessidade de execução de provas de conhecimento. Experimentos foram conduzidos para avaliar cada uma das fases do modelo. Os resultados dos experimentos mostraram que é factível avaliar a aquisição de conhecimento dentro de contextos pré-determinados e que há indícios de que alguns tipos de interações do usuário com os AVAs mantêm correlação com o nível de aprendizado do usuário. / The popularization of computational tools applied to teaching and the advent of Web 2.0 have led to the advancement of Virtual Learning Environments (VLE) through resources rendered by Virtual Reality (VR) and Augmented Reality (AR) technologies, leading to the emergence of Tridimensional VLEs (3D), which are widely employed in diverse fields of knowledge. In alliance with this advancement, the 3D VLE knowledge acquisition process has been the object of research studies which consider the conception of virtual environments. One of the discussions outlined in this context refers to the contribution that 3D VLEs effectively offer for knowledge acquisition and how it is possible to evaluate this learning process. Studies have demonstrated that methods widely employed for assessing cognition in 3D VLEs have made intense use of questionnaire application outside VLEs. It is possible to perceive that, in the evaluation process, the assessment tools applied in 3D VLEs do not incorporate the same interactive technologies available in the environment. Thus, the initial aim of this research is to identify the knowledge acquisition process in 3D VLEs, as well as existing methods for assessing if knowledge acquisition actually occurs and to which degree it occurs. From this study, the aim of the research is to define a method for assessing knowledge acquisition employing the same interactive technologies available in 3D VLEs, in an innovative manner, complementing widely used questionnaires as assessment tools. In addition to the suggestion of the conceptual method, an architecture was defined and a computational system capable of registering user interactions in 3D VLEs was implemented, in a non intrusive form of application. A mathematical model that offers learning assessment without the need of knowledge tests was also suggested. Experiments were conducted to evaluate each phase of the model. The results of the experiments show that it is feasible to evaluate knowledge acquisition within predetermined contexts and that there is evidence that some types of user interactions with VLEs are correlated with the user\'s learning level.

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Tourism has come to be recognised as a major contributor to national economies. In a knowledge-based economy (that emphasises the benefits of industry/government and academic research), a strong research base must underpin management of a tourist destination if it is to realise its full potential. The establishment of collaborative networks between industry, academia, and government in the strategic planning and management of cities and towns is becoming increasingly popular. However, the way in which the processes underlying these settings facilitate or inhibit eventual outcomes is poorly understood. If knowledge is to drive innovation and economic growth optimally, it is important not just to develop an understanding of the processes underlying the creation, diffusion and utilisation of knowledge in cooperative research settings, but also the relationships among them. Accordingly, the aim of this investigation is to examine the relationships among knowledge creation, diffusion and utilisation occurring in the Cooperative Research Centres (CRC) Program, specifically, the Gold Coast Visioning Project, with a view to identifying the most efficient means for formulating and disseminating research designed for industry and/or government application. Knowledge is defined as information that is imbued with meaning or relevance. However, this definition says little of the ways that individuals, groups and organisations acquire knowledge. While cognitive psychologists have produced several theories suggesting the structure and mechanisms of individual cognitive processes underlying the acquisition and use of knowledge, social scientists have sought to describe and explain the process by investigating the influence of social factors. Recent contributions to group learning have examined group composition, group size, familiarity among group members, and communication processes in an attempt to understand the ways in which groups acquire knowledge. Research shows that knowledge utilisation in organisations results from the interdependent influences of organisational processes and the control opportunities and control problems that arise through organisational structure. These frameworks provide accounts of how knowledge is utilised within an organisation, but not of how organisations learn. Recent research suggests that organisations learn through knowledge networks where organisational focus moves from the consideration and protection of boundaries to the management of (and care for) relationships. Therefore, organisations contain static (rules, norms and procedures) and dynamic (social relationships) elements that mutually influence the degree to which organisations learn. A synthesis of the available literature resulted in the development of a series of models that served not only to inform, but also be informed by the analysis of this investigation. A single case study, namely the Gold Coast Visioning Project, was used to examine the ways in which knowledge was created, disseminated and utilised in a CRC setting. This ethnographic investigation considered the process of knowledge creation through to utilisation at individual, group, organisational, and inter-organisational levels, while simultaneously examining the interrelated influences of social, cognitive, affective and communication factors. Throughout the project, data were collected through stakeholder interviews, various documents and participant observation of stakeholder meetings and workshops. Data were analysed using a grounded theory approach and methods of thick description. The results show that researchers and industry stakeholders bring different frames of reference, different expectations, and different knowledge bases to the exercise. This inhibited communication, and gave the appearance of dissension when, in fact, what was being sought was a common frame for understanding and communication. Additionally, the gap between industry and researcher worldviews generated the sense that industry was resisting or failing to understand what the research was seeking to achieve. Consequently, in order to manage the relationship, research plans and findings were communicated to industry in a teacher-to-student fashion, which fostered single-loop learning, and reduced industry stakeholders' sense of ownership in the process and findings. During the project, industry stakeholders frequently sought to have research come pre-packaged with "meaning", but researchers lacked the contextual knowledge necessary to specify the relevance of their research. The results also show that research findings need to be integrated and diffused to industry over time, and specific applications need to be formulated (and reformulated) in response to particular and changing needs of industry. As a result of this investigation, a model of 'best practice' has been developed with detailed recommendations for the design, implementation, and reporting of CRC-sponsored research to optimise its utility for end-users of such research. From a theoretical perspective, the findings of this study challenge the ways that current theories account for the ways in which knowledge is acquired and utilised since the results show that knowledge is constructed both socially and emotionally. Any investigation that seeks to understand how knowledge is acquired and utilised must consider social and affective influences. To ignore the role of emotion and values in the process of knowledge acquisition is to ignore a key component of an individual's reasoning capacity.

Feature selection is one of the important data preprocessing steps in data mining. The feature selection problem involves finding a feature subset such that a classification model built only with this subset would have better predictive accuracy than model built with a complete set of features. In this study, we propose two hybrid methods for feature selection. The best features are selected through either the hybrid methods or existing feature selection methods. Next, the reduced dataset is used to build classification models using five classifiers. The classification accuracy was evaluated in terms of the area under the Receiver Operating Characteristic (ROC) curve (AUC) performance metric. The proposed methods have been shown empirically to improve the performance of existing feature selection methods.