883 resultados para Knowledge organization systems


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Risk and knowledge are two concepts and components of business management which have so far been studied almost independently. This is especially true where risk management is conceived mainly in financial terms, as, for example, in the banking sector. The banking sector has sophisticated methodologies for managing risk, such as mathematical risk modeling. However. the methodologies for analyzing risk do not explicitly include knowledge management for risk knowledge creation and risk knowledge transfer. Banks are affected by internal and external changes with the consequent accommodation to new business models new regulations and the competition of big players around the world. Thus, banks have different levels of risk appetite and policies in risk management. This paper takes into consideration that business models are changing and that management is looking across the organization to identify the influence of strategic planning, information systems theory, risk management and knowledge management. These disciplines can handle the risks affecting banking that arise from different areas, but only if they work together. This creates a need to view them in an integrated way. This article sees enterprise risk management as a specific application of knowledge in order to control deviation from strategic objectives, shareholders' values and stakeholders' relationships. Before and after a modeling process it necessary to find insights into how the application of knowledge management processes can improve the understanding of risk and the implementation of enterprise risk management. The article presents a propose methodology to contribute to providing a guide for developing risk modeling knowledge and a reduction of knowledge silos, in order to improve the quality and quantity of solutions related to risk inquiries across the organization.

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The management and sharing of complex data, information and knowledge is a fundamental and growing concern in the Water and other Industries for a variety of reasons. For example, risks and uncertainties associated with climate, and other changes require knowledge to prepare for a range of future scenarios and potential extreme events. Formal ways in which knowledge can be established and managed can help deliver efficiencies on acquisition, structuring and filtering to provide only the essential aspects of the knowledge really needed. Ontologies are a key technology for this knowledge management. The construction of ontologies is a considerable overhead on any knowledge management programme. Hence current computer science research is investigating generating ontologies automatically from documents using text mining and natural language techniques. As an example of this, results from application of the Text2Onto tool to stakeholder documents for a project on sustainable water cycle management in new developments are presented. It is concluded that by adopting ontological representations sooner, rather than later in an analytical process, decision makers will be able to make better use of highly knowledgeable systems containing automated services to ensure that sustainability considerations are included.

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Purpose – This paper describes a “work in progress” research project being carried out with a public health care provider in the UK, a large NHS hospital Trust. Enhanced engagement with patients is one of the Trust’s core principles, but it is recognised that much more needs to be done to achieve this, and that ICT systems may be able to provide some support. The project is intended to find ways to better capture and evaluate the “voice of the patient” in order to lead to improvements in health care quality, safety and effectiveness. Design/methodology/approach – We propose to investigate the use of a patient-orientated knowledge management system (KMS) in managing knowledge about and from patients. The study is a mixed methods (quantitative and qualitative) investigation based on traditional action research, intended to answer the following three research questions: (1) How can a KMS be used as a mechanism to capture and evaluate patient experiences to provoke patient service change (2) How can the KMS assist in providing a mechanism for systematising patient engagement? (3) How can patient feedback be used to stimulate improvements in care, quality and safety? Originality/value –This methodology aims to involve patients at all phases of the study from its initial design onwards, thus leading to an understanding of the issues associated with using a KMS to manage knowledge about and for patients that is driven by the patients themselves. Practical implications – The outcomes of the project for the collaborating hospital will be firstly, a system for capturing and evaluating knowledge about and from patients, and then as a consequence, improved outcomes for both the patients and the service provider. More generally, it will produce a set of guidelines for managing patient knowledge in an NHS hospital that have been tested in one case example.

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Magnification can be provided to assist those with visual impairment to make the best use of remaining vision. Electronic transverse magnification of an object was first conceived for use in low vision in the late 1950s, but has developed slowly and is not extensively prescribed because of its relatively high cost and lack of portability. Electronic devices providing transverse magnification have been termed closed-circuit televisions (CCTVs) because of the direct cable link between the camera imaging system and monitor viewing system, but this description generally refers to surveillance devices and does not indicate the provision of features such as magnification and contrast enhancement. Therefore, the term Electronic Vision Enhancement Systems (EVES) is proposed to better distinguish and describe such devices. This paper reviews current knowledge on EVES for the visually impaired in terms of: classification; hardware and software (development of technology, magnification and field-of-view, contrast and image enhancement); user aspects (users and usage, reading speed and duration, and training); and potential future development of EVES. © 2003 The College of Optometrists.

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The management and sharing of complex data, information and knowledge is a fundamental and growing concern in the Water and other Industries for a variety of reasons. For example, risks and uncertainties associated with climate, and other changes require knowledge to prepare for a range of future scenarios and potential extreme events. Formal ways in which knowledge can be established and managed can help deliver efficiencies on acquisition, structuring and filtering to provide only the essential aspects of the knowledge really needed. Ontologies are a key technology for this knowledge management. The construction of ontologies is a considerable overhead on any knowledge management programme. Hence current computer science research is investigating generating ontologies automatically from documents using text mining and natural language techniques. As an example of this, results from application of the Text2Onto tool to stakeholder documents for a project on sustainable water cycle management in new developments are presented. It is concluded that by adopting ontological representations sooner, rather than later in an analytical process, decision makers will be able to make better use of highly knowledgeable systems containing automated services to ensure that sustainability considerations are included. © 2010 The authors.

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The problems of constructing the selfsrtucturized systems of memory of intelligence information processing tools, allowing formation of associative links in the memory, hierarchical organization and classification, generating concepts in the process of the information input, are discussed. The principles and methods for realization of selfstructurized systems on basis of hierarchic network structures of some special class – growing pyramidal network are studied. The algorithms for building, learning and recognition on basis of such type network structures are proposed. The examples of practical application are demonstrated.

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An ontological representation of buyer interests’ knowledge in process of e-commerce is proposed to use. It makes it more efficient to make a search of the most appropriate sellers via multiagent systems. An algorithm of a comparison of buyer ontology with one of e-shops (the taxonomies) and an e-commerce multiagent system are realised using ontology of information retrieval in distributed environment.

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The concept of knowledge is the central one used when solving the various problems of data mining and pattern recognition in finite spaces of Boolean or multi-valued attributes. A special form of knowledge representation, called implicative regularities, is proposed for applying in two powerful tools of modern logic: the inductive inference and the deductive inference. The first one is used for extracting the knowledge from the data. The second is applied when the knowledge is used for calculation of the goal attribute values. A set of efficient algorithms was developed for that, dealing with Boolean functions and finite predicates represented by logical vectors and matrices.

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A new original method and CASE-tool of system analysis and modelling are represented. They are for the first time consistent with the requirements of object-oriented technology of informational systems design. They essentially facilitate the construction of organisational systems models and increase the quality of the organisational designing and basic technological processes of object application developing.

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The paper deals with a problem of intelligent system’s design for complex environments. There is discussed a possibility to integrate several technologies into one basic structure. One possible structure is proposed in order to form a basis for intelligent system that would be able to operate in complex environments. The basic elements of the proposed structure have found their implemented in software system. This software system is shortly presented in the paper. The most important results of experiments are outlined and discussed at the end of the paper. Some possible directions of further research are sketched.

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In this work we suggest the technology of creation of intelligent tutoring systems which are oriented to teach knowledge. It is supposed the acquisition of expert’s knowledge by using of the Formal Concept Analysis method, then construction the test questions which are used for verification of the pupil's knowledge with the expert’s knowledge. Then the further tutoring strategy is generated by the results of this verification.

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In the article the theoretical aspects of planning of the systems of the controlled from distance diagnosing of level of know ledges of students are resulted on the basis of modern pedagogical theoretical and technological approaches. The practical results of creation of the systems of this type are resulted for organization of testing both in the structure of local networks of higher educational establishments and with access through the global network of Internet.

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Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

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Individuals often imitate each other to fall into the typical group, leading to a self-organized state of typical behaviors in a community. In this paper, we model self-organization in social tagging systems and illustrate the underlying interaction and dynamics. Specifically, we introduce a model in which individuals adjust their own tagging tendency to imitate the average tagging tendency. We found that when users are of low confidence, they tend to imitate others and lead to a self-organized state with active tagging. On the other hand, when users are of high confidence and are stubborn to change, tagging becomes inactive. We observe a phase transition at a critical level of user confidence when the system changes from one regime to the other. The distributions of post length obtained from the model are compared to real data, which show good agreement. © 2011 American Physical Society.