Planning and Coordination in Hierarchies of Intelligent Dynamic Systems

On the basis of the known principle of interactions prediction (Mesarovic), our earlier proposed incremental coordination principle is extended over hierarchical collectives of intelligent dynamic systems (IDSs) after Gennady Osipov. Such systems admit arbitrary types of variables in their state vector and thereby allow investigating more general dynamic systems than “classical” ones defined in numerical state spaces. Using the concept of effective N-attainability (Osipov), a straightforward procedure of planning for hierarchical collectives of IDS is developed. As soon as a plan for reaching a goal state from the current one is found, effective implementation of this plan requires for coordination of IDSs taking their parts in the collective. We consider both aspects of coordination (coordinability with respect to the coordinator’s task and coordinability in relation to the global task) and infer necessary conditions of the coordinability for a locally organized hierarchy of IDSs

DM model transformations framework

Metamodelling produces a \u27metamodel\u27 capable of generalizing the domain. A metamodel gathers all domain concepts and their relationships. It enables partitioning a domain problem into sub-problems. Decision makers can then develop a variety of domain solutions models based on mixing and matching solutions for sub-problems indentified using the metamodel. A repository of domain knowledge structured using the metamodel would allow the transformation of models generated from a higher level to a lower level according to scope of the problem on hand. In this paper, we reveal how a process of mixing and matching disaster management actions can be accomplished using our Disaster Management Metamodel (DMM). The paper describes DM model transformations underpinned by DMM. They are illustrated benefiting DM users creating appropriate DM solution models from extant partial solutions

Disaster Management (DM) Model Transformations Framework

Metamodelling produces a ‘metamodel’ capable of generalizing the domain. A metamodel gathers all domain concepts and their relationships. It enables partitioning a domain problem into sub-problems. Decision makers can then develop a variety of domain solutions models based on mixing and matching solutions for sub-problems indentified using the metamodel. A repository of domain knowledge structured using the metamodel would allow the transformation of models generated from a higher level to a lower level according to scope of the problem on hand. In this paper, we reveal how a process of mixing and matching disaster management actions can be accomplished using our Disaster Management Metamodel (DMM). The paper describes DM model transformations underpinned by DMM. They are illustrated benefiting DM users creating appropriate DM solution models from extant partial solutions

Computationally efficient ontology selection in software requirement planning

Understanding the needs of stakeholders and prioritizing requirements are the vital steps in the development of any software application. Enabling tools to support these steps have a critical role in the success of the corresponding software application. Based on such a critical role, this paper presents a computationally efficient ontology selection in software requirement planning. The key point guiding the underlying design is that, once gathered, requirements need to be processed by decomposition towards the generation of a specified systems design. A representational framework allows for the expression of high level abstract conceptions under a single schema, which may then be made explicit in terms of axiomatic relations and expressed in a suitable ontology. The initial experimental results indicate that our framework for filtered selection of a suitable ontology operates in a computationally efficient manner

Um método para a construção de taxonomias utilizando a DBpedia

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia e Gestão do Conhecimento, Florianópolis, 2017.O processo de criação de taxonomias demanda esforço de especialistas de domínio, engenheiros de taxonomias, investimento financeiro e tempo. Devido às limitações existentes em fornecer estes recursos em sua integralidade em diversas organizações, muitos projetos que envolvem a construção de taxonomias não atingem o êxito esperado. Este trabalho pretende auxiliar na construção de taxonomias através da proposição de um método automatizado para a sua construção. Para a construção deste método, foi adotada uma série de procedimentos metodológicos, que se iniciou com o levantamento do referencial teórico sobre taxonomias e sua construção. Em sequência, foi realizada uma busca sistemática no domínio de construção automatizada de taxonomias, buscando encontrar abordagens e procedimentos já existentes neste campo de estudo. A partir desta revisão, foi elaborado um método para a geração de taxonomias a partir de repositórios de informações textuais com o apoio de bases de conhecimento, que fornecem as relações hierárquicas para verificação das relações taxonômicas entre os termos. Uma implementação deste método em formato de software foi realizada, utilizando uma amostra de currículos da área de conhecimento das Ciências Agrárias cadastrados na Plataforma Lattes como repositório de informações. A versão em português da DBpedia foi adotada como base de conhecimento neste experimento. Esta implementação também adota um processo de reconhecimento de entidades para a descoberta dos termos relevantes que podem ser cadastrados nas taxonomias. As propostas de taxonomias geradas pela implementação foram comparadas estatisticamente com o tesauro AGROVOC, referência na área da agricultura. Com a análise, verificou-se que 60% a 80% dos termos encontrados nas taxonomias geradas pela implementação também estão presentes no AGROVOC, sendo esta oscilação pertinente aos parâmetros de filtragem informados na entrada do método, o repositório de informações textuais utilizado e a base de conhecimento empregada para validação das relações hierárquicas.Abstract : The process of creating taxonomies demands effort from domain experts, taxonomy engineers, financial investment and time. Due to the limitations of providing these resources in their entirety in several organizations, many projects that involve the construction of taxonomies do not achieve the expected success. This work intends to assist in the construction of taxonomies through the proposition of an automated method for its construction. For the construction of this method, a series of methodological procedures was adopted, which began with the survey of the theoretical reference on taxonomies and their construction. In sequence, a systematic search was made in the field of automated taxonomy construction, seeking to find approaches and procedures that already exist in this field of study. From this review, a method was developed for the generation of taxonomies from textual information repositories with the support of knowledge bases, which provide the hierarchical relationships for the verification of the taxonomic relations between the terms. An implementation of this method in software format was performed, using a sample of curricula from the Agrarian Sciences knowledge area registered in the Plataforma Lattes as a repository of information. The DBpedia?s Portuguese language version was adopted as knowledge base in this experiment. This implementation also adopts a process of entity recognition for the discovery of the relevant terms that can be registered in the taxonomies. The taxonomy proposals generated by the implementation were compared statistically with the AGROVOC thesaurus, reference in the area of agriculture. With the analysis, it was verified that 60% to 80% of the terms found in the taxonomies generated by the implementation are also present in AGROVOC, being this oscillation pertinent to the filter parameters informed in the method entry, the textual information repository used and the knowledge base used to validate hierarchical relationships

Providing metrics and automatic enhancement for hierarchical taxonomies

Taxonomies enable organising information in a human-machine understandable form, but constructing them for reuse and maintainability remains difficult. The paper presents a formal underpinning to provide quality metrics for a taxonomy under development. It proposes a methodology for semi-automatic building of maintainable taxonomies and outlines key features of the knowledge engineering context where the metrics and methodology are most suitable. The strength of the approach presented is that it is applied during the actual construction of the taxonomy. Users provide terms to describe different domain elements, as well as their attributes, and methodology uses metrics to assess the quality of this input. Changes according to given quality constraints are then proposed during the actual development of the taxonomy. © 2012 Elsevier Ltd. All rights reserved

Perspectivas da representação documental: discussão e experiências

Access to information is at the heart of the discussions of contemporary society, whether due to the multiplicity of infotechnological mechanisms that are geared to its generation and use, or through the arguments for promoting information for social and cultural democratization through citizen education. The Information Science, for consecrating the information as its object of research, systematizes, in the Documentary Representation, the critical and analytical study of theories, instruments, methods and methodologies that allow to make the information accessible. It is in this scope that this book is proposed, since it adds knowledge, concepts and applications of the relationship between Technology, Information and Representation for the consolidation of the Documentary Representation and that aims to promote debates about the consolidation of discussions and actions that involve the organization and the representation of the information resources, as well as the processes of data management in automated environment and its use. The discussions also envision the technological and media resources, through computational structures, which permeate the production, organization, distribution, access, storage, preservation, use and reuse of information resources through representation methods and recovery. It is understood, above all, the plurality of epistemological, theoretical and methodological conceptions present in Information Science. This book is, therefore, the result of efforts of researchers of the Documentary Representation and reflects research and teaching actions that imply the descriptive and thematic treatment of information