<p>Nowadays, more and more companies use Enterprise Models to integrate and coordinate their business processes with the aim of remaining competitive on the market. Consequently, Enterprise Models play a critical role in this integration enabling to improve the objectives of the enterprise, and ways to reach them in a given period of time. Through Enterprise Models, companies are able to improve the management of their operations, actors, processes and also to improve communication within the organisation.</p><p>This thesis describes another use of Enterprise Models. In this work, we intend to apply Enterprise Models as interface for information searching. The underlying needsfor this project lay in the fact that we would like to show that Enterprise Models canbe more than just models but it can be used in a more dynamic way which is through a software program for information searching. The software program aimed at, first,extracting the information contained in the Enterprise Models (which are stored into aXML file on the system). Once the information is extracted, it is used to express a query which will be sent into a search engine to retrieve some relevant document to the query and return them to the user.</p><p>The thesis was carried out over an entire academic semester. The results of this workare a report which summarizes all the knowledge gained into the field of the study. A software has been built to serve as a proof of testing the theories.</p>

The use of knowledge-based systems to aid in the diagnosis of faults in physical devices has grown considerably since their introduction during the 1970s. The majority of the early knowledge-based systems incorporated shallow knowledge, which sought to define simple cause and effect relationships between a symptom and a fault, that could be encoded as a set of rules. Though such systems enjoyed much success, it was recognised that they suffered from a number of inherent limitations such as inflexibility, inadequate explanation, and difficulties of knowledge elicitation. Many of these limitations can be overcome by developing knowledge-based systems which contain deeper knowledge about the device being diagnosed. Such systems, now generally referred to as model-based systems, have shown much promise, but there has been little evidence to suggest that they have successfully made the transition from the research centre to the workplace. This thesis argues that knowledge-based systems are an appropriate tool for the diagnosis of faults in complex devices, and that both deep and shallow knowledge have their part to play in this process. More specifically this thesis demonstrates how a wide-ranging knowledge-based system for quality assurance, based upon shallow knowledge, can be developed, and implemented. The resultant system, named DIPLOMA, not only diagnoses faults, but additionally provides advice and guidance on the assembly, disassembly, testing, inspection and repair of a highly complex hydro-mechanical device. Additionally it is shown that a highly innovative modelbased system, named MIDAS, can be used to contribute to the provision of diagnostic, explanatory and training facilities for the same hydro-mechanical device. The methods of designing, coding, implementing and evaluating both systems are explored in detail. The successful implementation and evaluation of the DIPLOMA and MIDAS systems has shown that knowledge-based systems are an appropriate tool for the diagnosis of faults in complex hydro-mechanical devices, and that they make a beneficial contribution to the business performance of the host organisation. Furthermore, it has been demonstrated that the most effective and comprehensive knowledge-based approach to fault diagnosis is one which incorporates both deep and shallow knowledge, so that the distinctive advantages of each can be realised in a single application. Finally, the research has provided evidence that the model-based approach to diagnosis is highly flexible, and may, therefore, be an appropriate technique for a wide range of industrial applications.

abstract: Clinical Decision Support (CDS) is primarily associated with alerts, reminders, order entry, rule-based invocation, diagnostic aids, and on-demand information retrieval. While valuable, these foci have been in production use for decades, and do not provide a broader, interoperable means of plugging structured clinical knowledge into live electronic health record (EHR) ecosystems for purposes of orchestrating the user experiences of patients and clinicians. To date, the gap between knowledge representation and user-facing EHR integration has been considered an “implementation concern” requiring unscalable manual human efforts and governance coordination. Drafting a questionnaire engineered to meet the specifications of the HL7 CDS Knowledge Artifact specification, for example, carries no reasonable expectation that it may be imported and deployed into a live system without significant burdens. Dramatic reduction of the time and effort gap in the research and application cycle could be revolutionary. Doing so, however, requires both a floor-to-ceiling precoordination of functional boundaries in the knowledge management lifecycle, as well as formalization of the human processes by which this occurs. This research introduces ARTAKA: Architecture for Real-Time Application of Knowledge Artifacts, as a concrete floor-to-ceiling technological blueprint for both provider heath IT (HIT) and vendor organizations to incrementally introduce value into existing systems dynamically. This is made possible by service-ization of curated knowledge artifacts, then injected into a highly scalable backend infrastructure by automated orchestration through public marketplaces. Supplementary examples of client app integration are also provided. Compilation of knowledge into platform-specific form has been left flexible, in so far as implementations comply with ARTAKA’s Context Event Service (CES) communication and Health Services Platform (HSP) Marketplace service packaging standards. Towards the goal of interoperable human processes, ARTAKA’s treatment of knowledge artifacts as a specialized form of software allows knowledge engineers to operate as a type of software engineering practice. Thus, nearly a century of software development processes, tools, policies, and lessons offer immediate benefit: in some cases, with remarkable parity. Analyses of experimentation is provided with guidelines in how choice aspects of software development life cycles (SDLCs) apply to knowledge artifact development in an ARTAKA environment. Portions of this culminating document have been further initiated with Standards Developing Organizations (SDOs) intended to ultimately produce normative standards, as have active relationships with other bodies. / Dissertation/Thesis / Doctoral Dissertation Biomedical Informatics 2018

Esse trabalho define K-Aspects (Knowledge Aspects), uma abordagem para a implementação de Sistemas de Conhecimento (SC) em linguagens orientadas a objetos usando o paradigma orientado a aspectos (OA) e anotações de metadados. Essa abordagem define uma forte correspondência entre o Modelo de Conhecimento (MC) e sua implementação no paradigma da orientação a objetos (OO). K-Aspects fornece um conjunto de anotações documentacionais para facilitar a leitura da associação entre o modelo de implementação e o modelo conceitual do conhecimento; um conjunto de anotações para facilitar a separação de interesses na implementação do SC usando OA; um conjunto de bibliotecas para realizar a interpretação das anotações e sua execução em aspectos; e uma ferramenta para geração de documentação do MC a partir das anotações no código. A abordagem busca atender tanto os engenheiros de conhecimento quanto os engenheiros de desenvolvimento em projetos de SC. Os engenheiros de conhecimento tem ao seu alcance um modo adequado para elaborar a especificação do MC que resulta em uma especificação em uma linguagem orientada a objetos, permitindo aos engenheiros de desenvolvimento implementarem o sistema preservando a estrutura do modelo conceitual e mantendo clara distinção entre os requisitos associados ao MC dos demais requisitos. K-Annotations adicionam recursos de OA ao modelo conceitual do conhecimento OO, oferecendo facilidades de tratamento separado de diversas funcionalidades transversais de um SC, através do particionamento do sistema em aspectos que implementam funcionalidades específicas, ativadas através das anotações inseridas no componente do modelo conceitual. Anotações distinguem, clara e visualmente, no código, os elementos do MC em relação ao restante do código do programa, facilitando a leitura do código pelos engenheiros de conhecimento. A função principal das anotações é prover as informações necessárias para a interpretação dos elementos de conhecimento durante a execução do programa. Anotações identificam as funcionalidades transversais relativas aos construtos do modelo e são gerenciadas pela biblioteca de aspectos. A abordagem foi validada re-escrevendo com o uso de K-Annotations um sistema de conhecimento no domínio da análise da qualidade de reservatórios de petróleo. O modelo desse sistema representa uma ontologia de domínio sobre o qual métodos de solução de problemas para interpretação e classificação de rochas são aplicados. A análise dos resultados identificou um conjunto de vantagens no uso de K-Aspects, como distinção clara entre a implementação do MC e a implementação dos demais requisitos, suporte nativo aos construtos providos no modelo de conhecimento e alto grau de rastreabilidade entre o modelo e sua implementação. Além disso, provê redução de tarefas repetitivas de implementação e redução da dispersão de código a partir da geração automática de código. As bibliotecas de aspectos garantem o encapsulamento de inferências e tarefas. As bibliotecas tratam os construtos do modelo para garantir a reutilização em diferentes projetos de SCs. / This work defines K-Aspects (Knowledge Aspects), an approach for implementing Knowledge Systems (KS) with object-oriented languages using the aspect-oriented paradigm (AO) and metadata annotations. This approach defines a strong link between the knowledge model (KM) and its implementation in the object-oriented paradigm (OO). K-Aspects provides a set of documentational annotations to make the association between the implementation model and the knowledge conceptual model easier to read; a set of annotations to enable the separation of concerns, using aspect orientation, of the implementation of the different requirements of the knowledge system; a set of libraries to perform the interpretation and execution as aspects of annotations; and a tool for documentation generation of the KM extracted from the annotations on the code. The approach aims to support both knowledge engineers and development engineers in KS projects, by providing to the knowledge engineers a well-defined way to elaborate the KS specification, which results in a specification presented in an object oriented language, making it easily understandable and extensible by development engineers that can thus implement the knowledge system preserving its conceptual knowledge structure and keeping a clear distinction of the requirements associated to the KM from the other requirements. K-Annotations add aspect oriented resources to the OO conceptual knowledge model, providing features to manage separately the multiple crosscutting concerns of a KS, partitioning the system in aspects that implement specific features, activated by annotations inserted in the knowledge conceptual model. Annotations distinguish, clearly and visually, within the code, KM elements from the rest of the code, making easier the code reading by the knowledge engineers. The most important function of the annotations is to provide information necessary for interpreting knowledge elements during runtime. Annotations identify several crosscutting concerns related to the model constructs. Annotations are managed and executed by the aspect libraries. This approach was validated by re-coding, using K-Annotations, a complex commercial KS on the domain of oil reservoir quality analysis. The model of this system represents a domain ontology on which problem-resolving methods for rock interpretation and classification are performed. The analysis of the results identified several advantages of using K-Aspects as: a clear distinction of the KM implementation among other requirements; native support for knowledge model constructs; and high traceability between the knowledge conceptual model and its implementation. Moreover, the use of K-Aspects reduces repetitive implementation tasks and code dispersion because of the automatic code generation. The provided aspect libraries enable the encapsulation of inferences and the execution of several tasks. The libraries manage the constructs of the model thus providing reusability among multiple KS projects.

Esse trabalho define K-Aspects (Knowledge Aspects), uma abordagem para a implementação de Sistemas de Conhecimento (SC) em linguagens orientadas a objetos usando o paradigma orientado a aspectos (OA) e anotações de metadados. Essa abordagem define uma forte correspondência entre o Modelo de Conhecimento (MC) e sua implementação no paradigma da orientação a objetos (OO). K-Aspects fornece um conjunto de anotações documentacionais para facilitar a leitura da associação entre o modelo de implementação e o modelo conceitual do conhecimento; um conjunto de anotações para facilitar a separação de interesses na implementação do SC usando OA; um conjunto de bibliotecas para realizar a interpretação das anotações e sua execução em aspectos; e uma ferramenta para geração de documentação do MC a partir das anotações no código. A abordagem busca atender tanto os engenheiros de conhecimento quanto os engenheiros de desenvolvimento em projetos de SC. Os engenheiros de conhecimento tem ao seu alcance um modo adequado para elaborar a especificação do MC que resulta em uma especificação em uma linguagem orientada a objetos, permitindo aos engenheiros de desenvolvimento implementarem o sistema preservando a estrutura do modelo conceitual e mantendo clara distinção entre os requisitos associados ao MC dos demais requisitos. K-Annotations adicionam recursos de OA ao modelo conceitual do conhecimento OO, oferecendo facilidades de tratamento separado de diversas funcionalidades transversais de um SC, através do particionamento do sistema em aspectos que implementam funcionalidades específicas, ativadas através das anotações inseridas no componente do modelo conceitual. Anotações distinguem, clara e visualmente, no código, os elementos do MC em relação ao restante do código do programa, facilitando a leitura do código pelos engenheiros de conhecimento. A função principal das anotações é prover as informações necessárias para a interpretação dos elementos de conhecimento durante a execução do programa. Anotações identificam as funcionalidades transversais relativas aos construtos do modelo e são gerenciadas pela biblioteca de aspectos. A abordagem foi validada re-escrevendo com o uso de K-Annotations um sistema de conhecimento no domínio da análise da qualidade de reservatórios de petróleo. O modelo desse sistema representa uma ontologia de domínio sobre o qual métodos de solução de problemas para interpretação e classificação de rochas são aplicados. A análise dos resultados identificou um conjunto de vantagens no uso de K-Aspects, como distinção clara entre a implementação do MC e a implementação dos demais requisitos, suporte nativo aos construtos providos no modelo de conhecimento e alto grau de rastreabilidade entre o modelo e sua implementação. Além disso, provê redução de tarefas repetitivas de implementação e redução da dispersão de código a partir da geração automática de código. As bibliotecas de aspectos garantem o encapsulamento de inferências e tarefas. As bibliotecas tratam os construtos do modelo para garantir a reutilização em diferentes projetos de SCs. / This work defines K-Aspects (Knowledge Aspects), an approach for implementing Knowledge Systems (KS) with object-oriented languages using the aspect-oriented paradigm (AO) and metadata annotations. This approach defines a strong link between the knowledge model (KM) and its implementation in the object-oriented paradigm (OO). K-Aspects provides a set of documentational annotations to make the association between the implementation model and the knowledge conceptual model easier to read; a set of annotations to enable the separation of concerns, using aspect orientation, of the implementation of the different requirements of the knowledge system; a set of libraries to perform the interpretation and execution as aspects of annotations; and a tool for documentation generation of the KM extracted from the annotations on the code. The approach aims to support both knowledge engineers and development engineers in KS projects, by providing to the knowledge engineers a well-defined way to elaborate the KS specification, which results in a specification presented in an object oriented language, making it easily understandable and extensible by development engineers that can thus implement the knowledge system preserving its conceptual knowledge structure and keeping a clear distinction of the requirements associated to the KM from the other requirements. K-Annotations add aspect oriented resources to the OO conceptual knowledge model, providing features to manage separately the multiple crosscutting concerns of a KS, partitioning the system in aspects that implement specific features, activated by annotations inserted in the knowledge conceptual model. Annotations distinguish, clearly and visually, within the code, KM elements from the rest of the code, making easier the code reading by the knowledge engineers. The most important function of the annotations is to provide information necessary for interpreting knowledge elements during runtime. Annotations identify several crosscutting concerns related to the model constructs. Annotations are managed and executed by the aspect libraries. This approach was validated by re-coding, using K-Annotations, a complex commercial KS on the domain of oil reservoir quality analysis. The model of this system represents a domain ontology on which problem-resolving methods for rock interpretation and classification are performed. The analysis of the results identified several advantages of using K-Aspects as: a clear distinction of the KM implementation among other requirements; native support for knowledge model constructs; and high traceability between the knowledge conceptual model and its implementation. Moreover, the use of K-Aspects reduces repetitive implementation tasks and code dispersion because of the automatic code generation. The provided aspect libraries enable the encapsulation of inferences and the execution of several tasks. The libraries manage the constructs of the model thus providing reusability among multiple KS projects.

Esse trabalho define K-Aspects (Knowledge Aspects), uma abordagem para a implementação de Sistemas de Conhecimento (SC) em linguagens orientadas a objetos usando o paradigma orientado a aspectos (OA) e anotações de metadados. Essa abordagem define uma forte correspondência entre o Modelo de Conhecimento (MC) e sua implementação no paradigma da orientação a objetos (OO). K-Aspects fornece um conjunto de anotações documentacionais para facilitar a leitura da associação entre o modelo de implementação e o modelo conceitual do conhecimento; um conjunto de anotações para facilitar a separação de interesses na implementação do SC usando OA; um conjunto de bibliotecas para realizar a interpretação das anotações e sua execução em aspectos; e uma ferramenta para geração de documentação do MC a partir das anotações no código. A abordagem busca atender tanto os engenheiros de conhecimento quanto os engenheiros de desenvolvimento em projetos de SC. Os engenheiros de conhecimento tem ao seu alcance um modo adequado para elaborar a especificação do MC que resulta em uma especificação em uma linguagem orientada a objetos, permitindo aos engenheiros de desenvolvimento implementarem o sistema preservando a estrutura do modelo conceitual e mantendo clara distinção entre os requisitos associados ao MC dos demais requisitos. K-Annotations adicionam recursos de OA ao modelo conceitual do conhecimento OO, oferecendo facilidades de tratamento separado de diversas funcionalidades transversais de um SC, através do particionamento do sistema em aspectos que implementam funcionalidades específicas, ativadas através das anotações inseridas no componente do modelo conceitual. Anotações distinguem, clara e visualmente, no código, os elementos do MC em relação ao restante do código do programa, facilitando a leitura do código pelos engenheiros de conhecimento. A função principal das anotações é prover as informações necessárias para a interpretação dos elementos de conhecimento durante a execução do programa. Anotações identificam as funcionalidades transversais relativas aos construtos do modelo e são gerenciadas pela biblioteca de aspectos. A abordagem foi validada re-escrevendo com o uso de K-Annotations um sistema de conhecimento no domínio da análise da qualidade de reservatórios de petróleo. O modelo desse sistema representa uma ontologia de domínio sobre o qual métodos de solução de problemas para interpretação e classificação de rochas são aplicados. A análise dos resultados identificou um conjunto de vantagens no uso de K-Aspects, como distinção clara entre a implementação do MC e a implementação dos demais requisitos, suporte nativo aos construtos providos no modelo de conhecimento e alto grau de rastreabilidade entre o modelo e sua implementação. Além disso, provê redução de tarefas repetitivas de implementação e redução da dispersão de código a partir da geração automática de código. As bibliotecas de aspectos garantem o encapsulamento de inferências e tarefas. As bibliotecas tratam os construtos do modelo para garantir a reutilização em diferentes projetos de SCs. / This work defines K-Aspects (Knowledge Aspects), an approach for implementing Knowledge Systems (KS) with object-oriented languages using the aspect-oriented paradigm (AO) and metadata annotations. This approach defines a strong link between the knowledge model (KM) and its implementation in the object-oriented paradigm (OO). K-Aspects provides a set of documentational annotations to make the association between the implementation model and the knowledge conceptual model easier to read; a set of annotations to enable the separation of concerns, using aspect orientation, of the implementation of the different requirements of the knowledge system; a set of libraries to perform the interpretation and execution as aspects of annotations; and a tool for documentation generation of the KM extracted from the annotations on the code. The approach aims to support both knowledge engineers and development engineers in KS projects, by providing to the knowledge engineers a well-defined way to elaborate the KS specification, which results in a specification presented in an object oriented language, making it easily understandable and extensible by development engineers that can thus implement the knowledge system preserving its conceptual knowledge structure and keeping a clear distinction of the requirements associated to the KM from the other requirements. K-Annotations add aspect oriented resources to the OO conceptual knowledge model, providing features to manage separately the multiple crosscutting concerns of a KS, partitioning the system in aspects that implement specific features, activated by annotations inserted in the knowledge conceptual model. Annotations distinguish, clearly and visually, within the code, KM elements from the rest of the code, making easier the code reading by the knowledge engineers. The most important function of the annotations is to provide information necessary for interpreting knowledge elements during runtime. Annotations identify several crosscutting concerns related to the model constructs. Annotations are managed and executed by the aspect libraries. This approach was validated by re-coding, using K-Annotations, a complex commercial KS on the domain of oil reservoir quality analysis. The model of this system represents a domain ontology on which problem-resolving methods for rock interpretation and classification are performed. The analysis of the results identified several advantages of using K-Aspects as: a clear distinction of the KM implementation among other requirements; native support for knowledge model constructs; and high traceability between the knowledge conceptual model and its implementation. Moreover, the use of K-Aspects reduces repetitive implementation tasks and code dispersion because of the automatic code generation. The provided aspect libraries enable the encapsulation of inferences and the execution of several tasks. The libraries manage the constructs of the model thus providing reusability among multiple KS projects.

Made available in DSpace on 2016-08-17T16:54:32Z (GMT). No. of bitstreams: 1 Tese Carla.pdf: 23507425 bytes, checksum: b08fca6c8eacdc0fd5d075a385f235e5 (MD5) Previous issue date: 2013-06-05 / Knowledge systems are a suitable computational approach to solve complex problems and to provide decision support. Ontologies are an approach for knowledge representation about an application domain, allowing the semantic processing of information and, through more precise interpretation of information, turning systems more effective and usable. Ontology Population looks for instantiating the constituent elements of an ontology, like properties and non-taxonomic relationships. Manual population by domain experts and knowledge engineers is an expensive and time consuming task. Fast ontology population is critical for the success of knowledge-based applications. Thus, automatic or semi-automatic approaches are needed. This work proposes a generic process for Automatic Ontology Population by specifying its phases and the techniques used to perform the activities on each phase. It also proposes a domain-independent process for automatic population of ontologies (DIAOPPro) from text that applies natural language processing and information extraction techniques to acquire and classify ontology instances. This is a new approach for automatic ontology population that uses an ontology to automatically generate rules to extract instances from text and classify them in ontology classes. These rules can be generated from ontologies of any domain, making the proposed process domain independent. To evaluate DIAOP-Pro four case studies were conducted to demonstrate its effectiveness and feasibility. In the first one we evaluated the effectiveness of phase "Identification of Candidate instances" comparing the results obtained by applying statistical techniques with those of purely linguistic techniques. In the second experiment we evaluated the feasibility of the phase "Construction of a Classifier", through the automatic generation of a classifier. The last two experiments evaluated the effectiveness of DIAOP-Pro into two distinct domains: the legal and the tourism domains. The results indicate that our approach can extract and classify instances with high effectiveness with the additional advantage of domain independence. / A demanda por sistemas baseado em conhecimento é crescente considerando suas aptidões para a solução de problemas complexos e para a tomada de decisão. As ontologias são formalismos para a representação de conhecimento de um dado domínio, que permitem o processamento semântico das informações e, através de interpretações mais precisas das informações, os sistemas apresentam maior efetividade e usabilidade. O povoamento de ontologias visa a instanciação de propriedades e relacionamentos não taxonômicos de classes de ontologias. Entretanto, o povoamento manual de ontologias por especialistas de domínio e engenheiros do conhecimemto é uma tarefa cara e que consome muito tempo. O povoamento de ontologias rápido e com baixo custo é crucial para o sucesso de aplicações baseadas em conhecimento. Portanto, torna-se fundamental uma semi-automatização ou automatização desse processo. Esta tese propõe um processo genérico para o problema do Povoamento Automático de Ontologias, especificando suas fases e técnicas que podem ser aplicadas em cada uma delas. É também proposto um Processo Independente de Domínio para o Povoamento Automático de Ontologias (DIAOP-Pro) a partir de fontes textuais, que aplica técnicas de processamento da linguagem natural e extração de informação para adquirir e classificar instâncias de ontologias. O DIAOP-Pro se constitui em uma abordagem original uma vez que propõe o povoamento automático de ontologias utilizando uma ontologia para a geração automática de regras para extrair instâncias a partir de textos e classifica-as como instâncias de classes da ontologia. Estas regras podem ser geradas a partir de ontologias específicas de qualquer domínio, tornando o processo independente de domínio. Para avaliar o processo DIAOP-Pro foram conduzidos quatro estudos de caso de modo a demonstrar a sua efetividade e viabilidade. O primeiro estudo de caso foi realizado para avaliar a efetividade da fase Identificação de Instâncias Candidatas , no qual foram comparados os resultados obtidos com a aplicação de técnicas estatísticas e de técnicas puramente lingüísticas. O segundo estudo de caso foi realizado para avaliar a viabiliadade da fase Construção de um Classificador , através da experimentação com a geração automática do classificador. O terceiro e o quarto estudo de caso foram realizados para avaliar a efetividade do processo proposto em dois domínios distintos, o jurídico e o turístico. Os resultados indicam que o processo DIAOP-Pro povoa ontologias específicas de qualquer domínio com boa efetividade e com a vantagem adicional da independência do domínio.

Nowadays, more and more companies use Enterprise Models to integrate and coordinate their business processes with the aim of remaining competitive on the market. Consequently, Enterprise Models play a critical role in this integration enabling to improve the objectives of the enterprise, and ways to reach them in a given period of time. Through Enterprise Models, companies are able to improve the management of their operations, actors, processes and also to improve communication within the organisation. This thesis describes another use of Enterprise Models. In this work, we intend to apply Enterprise Models as interface for information searching. The underlying needsfor this project lay in the fact that we would like to show that Enterprise Models canbe more than just models but it can be used in a more dynamic way which is through a software program for information searching. The software program aimed at, first,extracting the information contained in the Enterprise Models (which are stored into aXML file on the system). Once the information is extracted, it is used to express a query which will be sent into a search engine to retrieve some relevant document to the query and return them to the user. The thesis was carried out over an entire academic semester. The results of this workare a report which summarizes all the knowledge gained into the field of the study. A software has been built to serve as a proof of testing the theories.

This thesis discusses how Multi-agent Systems (MAS) should be designed in the context of diabetic health care. Three fields are touched: computer science, socio-psychology and systems science. Agent Technology is the core technology in the research. Theories from socio-psychology and systems science are applied to facilitate the discussion about computer agents. As the integration of socio-psychology and systems science, Activity Systems Theory is introduced to give a synthesized description of MAS. Laws and models are introduced with benefits on both individual agent and agent communities. Cybernetics from systems science and knowledge engineering from computer science are introduced to approach the design and implementation of the individual agent architecture. A computer agent is considered intelligent if it is capable of reactivity, proactivity and social activity. Reactivity and proactivity can be realized through a cybernetic approach. Social activity is much more complex, since it considers MAS coordination. In this thesis, I discuss it from the perspectives of socio-psychology. The hierarchy and motivation thinking from Activity Systems Theory is introduced to the MAS coordination. To behave intelligent, computer agents should work with knowledge. Knowledge is considered as a run-time property of a group of agents (MAS). During the MAS coordination, agents generate new information through exchanging the information they have. A knowledge component is needed in agent’s architecture for the knowledge related tasks. In my research, I adopt CommonKADS methodology for the design and implementation of agent’s knowledge component. The contribution of this research is twofold: first, MAS coordination is described with perspectives from socio-psychology. According to Activity Systems Theory, MAS is hierarchically organized and driven by the motivation. This thesis introduces a motivation-driven mechanism for the MAS coordination. Second, the research project Integrated Mobile Information Systems for health care (IMIS) indicates that the diabetic health care can be improved by introducing agent-based services to the care-providers and care-receivers. IMIS agents are designed with capabilities of information sharing, organization coordination and task delegation. To perform these tasks, the IMIS agents interact with each other based on the coordination mechanism that is discussed above.

Les brevets d’invention titres de propriété industrielle confèrent à leurs titulaires le monopole de l’invention brevetée. On peut y trouver une sorte d’historique de l’évolution de l’artefact. Dans ce contexte le concepteur est très souvent amené à faire des recherches dans les documents de brevets afin de bénéficier des connaissances qui y sont contenues en vue de structurer le processus inventif. Développée pour assister les concepteurs dans leur démarche d’innovation, la Méthode de Conception Inventive (MCI), s’inscrit dans le modèle de la dialectique. La MCI a précisé les concepts entrant en jeu dans la description des évolutions des systèmes techniques et des artefacts. Ces items intéressent bien souvent les concepteurs et sont essentiels à la compréhension du problème sous-jacent et à la collecte de toutes les caractéristiques sur lesquelles on peut agir ; et de l’effet de leurs variations sur l’artefact. Cette thèse consiste d’abord à analyser le document de brevet d’un point de vue linguistique, afin d’en connaitre la typologie. Il s’agit, ensuite, de repérer dans le document de brevets les connaissances susceptibles d’être utiles à la MCI et à les formaliser sous forme de programme informatique. L’approche que nous proposons est issue du text-mining. Elle est à base de marqueurs linguistiques et utilise des patrons lexico-syntaxiques issus du domaine du traitement automatique des langues. Cette méthode d’extraction des concepts utiles à la MCI permet l’établissement d’une sorte de cartographie initiale des évolutions passées et possibles des caractéristiques de l’artefact. L’intérêt est en outre de faciliter grandement l’analyse préliminaire des connaissances relative au dit artefact. / Patents are industrial property titles that give their holders a monopoly over the patented invention. It is possible to find a sort of history of the evolution of the artifact. In this context the designer often like to do research in patent documents in order to benefit from the knowledge contained inside to structure the inventive process. Developed to assist designers in their innovation approach, the Inventive Design Method (IDM) is part of the pattern of dialectic. IDM has clarified the concepts at stake in the description of the evolution of technical systems and artifact. These items often interest designers and are essential to understanding the underlying problem and collecting of all features on which to act; and the effect of variations on the artifact. This thesis, firstly, deals with patent document analysis from a linguistic point of view, in order to know its typology. Then, it is possible to identify in the patent document, the knowledge likely to be useful to IDM and formalize it as a computer program. The approach proposed in this paper is based on text mining techniques. It uses a method based on linguistic markers using lexical and syntactic patterns from the field of natural language processing. This method of extraction of useful concepts for IDM allows the establishment of a kind of initial mapping of past and possible changes in the future of the artifact characteristics. The interest is also to greatly facilitate the preliminary analysis of knowledge on the said artifact.