CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Learning Components of Computational Models from Texts

The mental models of experts can be encoded in computational cognitive models that can support the functioning of intelligent agents. This paper compares human mental models to computational cognitive models, and explores the extent to which the latter can be acquired automatically from published sources via automatic learning by reading. It suggests that although model components can be automatically learned, published sources lack sufficient information for the compilation of fully specified models that can support sophisticated agent capabilities, such as physiological simulation and reasoning. Such models require hypotheses and educated guessing about unattested phenomena, which can be provided only by humans and are best recorded using knowledge engineering strategies. This work merges past work on cognitive modeling, agent simulation, learning by reading, and narrative structure, and draws examples from the domain of clinical medicine

Feature-based validation reasoning for intent-driven engineering design

Feature based modelling represents the future of CAD systems. However, operations such as modelling and editing can corrupt the validity of a feature-based model representation. Feature interactions are a consequence of feature operations and the existence of a number of features in the same model. Feature interaction affects not only the solid representation of the part, but also the functional intentions embedded within features. A technique is thus required to assess the integrity of a feature-based model from various perspectives, including the functional intentional one, and this technique must take into account the problems brought about by feature interactions and operations. The understanding, reasoning and resolution of invalid feature-based models requires an understanding of the feature interaction phenomena, as well as the characterisation of these functional intentions. A system capable of such assessment is called a feature-based representation validation system. This research studies feature interaction phenomena and feature-based designer's intents as a medium to achieve a feature-based representation validation system. [Continues.

Information Systems as Representations: A Review of the Theory and Evidence

Representation theory proposes that the basic purpose of an information system (IS) is to faithfully represent certain real-world phenomena, allowing users to reason about these phenomena more cost- effectively than if they were observed directly. Over the past three decades, the theory has underpinned much research on conceptual modeling in IS analysis and design and, increasingly, research on other IS phenomena such as data quality, system alignment, IS security, and system use. The original theory has also inspired further development of its core premises and advances in methodological guidelines to improve its use and evaluation. Nonetheless, the theory has attracted repeated criticisms regarding its validity, relevance, usefulness, and robustness. Given the burgeoning literature on the theory over time, both positive and negative, the time is ripe for a narrative, developmental review. We review representation theory, examine how it has been used, and critically evaluate its contributions and limitations. Based on our findings, we articulate a set of recommendations for improving its application, development, testing, and evaluation

Designing Digital Work

Combining theory, methodology and tools, this open access book illustrates how to guide innovation in today’s digitized business environment. Highlighting the importance of human knowledge and experience in implementing business processes, the authors take a conceptual perspective to explore the challenges and issues currently facing organizations. Subsequent chapters put these concepts into practice, discussing instruments that can be used to support the articulation and alignment of knowledge within work processes. A timely and comprehensive set of tools and case studies, this book is essential reading for those researching innovation and digitization, organization and business strategy

Traveling of Requirements in the Development of Packaged Software: An Investigation of Work Design and Uncertainty

Software requirements, and how they are constructed, shared and translated across software organizations, express uncertainties that software developers need to address through appropriate structuring of the process and the organization at large. To gain new insights into this important phenomenon, we rely on theory of work design and the travelling metaphor to undertake an in-depth qualitative inquiry into recurrent development of packaged software for the utility industry. Using the particular context of software provider GridCo, we examine how requirements are constructed, shared, and translated as they travel across vertical and horizontal boundaries. In revealing insights into these practices, we contribute to theory by conceptualizing how requirements travel, not just locally, but across organizations and time, thereby uncovering new knowledge about the responses to requirement uncertainty in development of packaged software. We also contribute to theory by providing narrative accounts of in situ requirements processes and by revealing practical consequences of organization structure on managing uncertainty

identifying archaeological knowledge using multi dimensional scaling and multiple constraint satisfaction

In this thesis, I look at the current state of research in two fields: the cognitive psychology of learning and expertise & the development of Intelligent Tutoring Systems, especially their methods of modelling the users knowledge state. Within these areas I proceed to examine the way that these theories have overlapped in the past and consider their recent divergence, suggesting that this parting of the ways is premature. I then consider other relevent research so as to suggest a hypothesis where a symbolic connectionist approach to the modelling of knowledge states could be a solution to previous difficulties in the field of Intelligent Tutoring. This hypothesis is then used to construct a method for its examination and also a computer program to analyse the collected data. I then undertake experimental work to validate my hypothesis, and compare my results and methods with a pre-established technique for interpreting the data, that of multi-dimensional scaling. Finally the method now shown to be feasible is discussed to indicate the its success and highlight its shortcomings. Further suggestions are also made as to further research avenues

Semantically intelligent semi-automated ontology integration

An ontology is a way of information categorization and storage. Web Ontologies provide help in retrieving the required and precise information over the web. However, the problem of heterogeneity between ontologies may occur in the use of multiple ontologies of the same domain. The integration of ontologies provides a solution for the heterogeneity problem. Ontology integration is a solution to problem of interoperability in the knowledge based systems. Ontology integration provides a mechanism to find the semantic association between a pair of reference ontologies based on their concepts. Many researchers have been working on the problem of ontology integration; however, multiple issues related to ontology integration are still not addressed. This dissertation involves the investigation of the ontology integration problem and proposes a layer based enhanced framework as a solution to the problem. The comparison between concepts of reference ontologies is based on their semantics along with their syntax in the concept matching process of ontology integration. The semantic relationship of a concept with other concepts between ontologies and the provision of user confirmation (only for the problematic cases) are also taken into account in this process. The proposed framework is implemented and validated by providing a comparison of the proposed concept matching technique with the existing techniques. The test case scenarios are provided in order to compare and analyse the proposed framework in the analysis phase. The results of the experiments completed demonstrate the efficacy and success of the proposed framework