116 resultados para Knowledge Management Tools

em Aston University Research Archive


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With this paper, we propose a set of techniques to largely automate the process of KA, by using technologies based on Information Extraction (IE) , Information Retrieval and Natural Language Processing. We aim to reduce all the impeding factors mention above and thereby contribute to the wider utility of the knowledge management tools. In particular we intend to reduce the introspection of knowledge engineers or the extended elicitations of knowledge from experts by extensive textual analysis using a variety of methods and tools, as texts are largely available and in them - we believe - lies most of an organization's memory.

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Purpose - To consider the role of technology in knowledge management in organizations, both actual and desired. Design/methodology/approach - Facilitated, computer-supported group workshops were conducted with 78 people from ten different organizations. The objective of each workshop was to review the current state of knowledge management in that organization and develop an action plan for the future. Findings - Only three organizations had adopted a strongly technology-based "solution" to knowledge management problems, and these followed three substantially different routes. There was a clear emphasis on the use of general information technology tools to support knowledge management activities, rather than the use of tools specific to knowledge management. Research limitations/implications - Further research is needed to help organizations make best use of generally available software such as intranets and e-mail for knowledge management. Many issues, especially human, relate to the implementation of any technology. Participation was restricted to organizations that wished to produce an action plan for knowledge management. The findings may therefore represent only "average" organizations, not the very best practice. Practical implications - Each organization must resolve four tensions: Between the quantity and quality of information/knowledge, between centralized and decentralized organization, between head office and organizational knowledge, and between "push" and "pull" processes. Originality/value - Although it is the group rather than an individual that determines what counts as knowledge, hardly any previous studies of knowledge management have collected data in a group context.

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While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic mark-up. In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. This analysis shows that, while there is still some way to go before semantic annotation tools will be able to address fully all the knowledge management needs, research in the area is active and making good progress.

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Ontologies have become widely accepted as the main method for representing knowledge in Knowledge Management (KM) applica-tions. Given the continuous and rapid change and dynamic nature of knowledge in all fields, automated methods for construct-ing ontologies are of great importance. All ontologies or taxonomies currently in use have been hand built and require consider-able manpower to keep up to date. Taxono-mies are less logically rigorous than ontolo-gies, and in this paper we consider the re-quirements for a system which automatically constructed taxonomies. There are a number of potentially useful methods for construct-ing hierarchically organised concepts from a collection of texts and there are a number of automatic methods which permit one to as-sociate one word with another. The impor-tant issue for the successful development of this research area is to identify techniques for labelling the relation between two candi-date terms, if one exists. We consider a number of possible approaches and argue that the majority are unsuitable for our re-quirements.

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Automatic ontology building is a vital issue in many fields where they are currently built manually. This paper presents a user-centred methodology for ontology construction based on the use of Machine Learning and Natural Language Processing. In our approach, the user selects a corpus of texts and sketches a preliminary ontology (or selects an existing one) for a domain with a preliminary vocabulary associated to the elements in the ontology (lexicalisations). Examples of sentences involving such lexicalisation (e.g. ISA relation) in the corpus are automatically retrieved by the system. Retrieved examples are validated by the user and used by an adaptive Information Extraction system to generate patterns that discover other lexicalisations of the same objects in the ontology, possibly identifying new concepts or relations. New instances are added to the existing ontology or used to tune it. This process is repeated until a satisfactory ontology is obtained. The methodology largely automates the ontology construction process and the output is an ontology with an associated trained leaner to be used for further ontology modifications.

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Electronic information tools have become increasingly popular with channel manufacturers in their efforts to manage resellers. Although these tools have been found to increase the efficiency of communications, researchers and practitioners alike have questioned their effectiveness. To investigate how top-down electronic information affects social channel relationships we consider the use of such tools in information technology distribution channels. Using electronic communications theory and channel governance theory we hypothesize that the usefulness of the tools is a function of the type of information inherent in each tool (demand creation information or supply fulfillment information) and the particular communications characteristics of this information.

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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 (RM) is conceived mainly in financial terms, as for example, in the financial institutions sector. Financial institutions are affected by internal and external changes with the consequent accommodation to new business models, new regulations and new global competition that includes new big players. These changes induce financial institutions to develop different methodologies for managing risk, such as the enterprise risk management (ERM) approach, in order to adopt a holistic view of risk management and, consequently, to deal with different types of risk, levels of risk appetite, and policies in risk management. However, the methodologies for analysing risk do not explicitly include knowledge management (KM). This research examines the potential relationships between KM and two RM concepts: perceived quality of risk control and perceived value of ERM. To fulfill the objective of identifying how KM concepts can have a positive influence on some RM concepts, a literature review of KM and its processes and RM and its processes was performed. From this literature review eight hypotheses were analysed using a classification into people, process and technology variables. The data for this research was gathered from a survey applied to risk management employees in financial institutions and 121 answers were analysed. The analysis of the data was based on multivariate techniques, more specifically stepwise regression analysis. The results showed that the perceived quality of risk control is significantly associated with the variables: perceived quality of risk knowledge sharing, perceived quality of communication among people, web channel functionality, and risk management information system functionality. However, the relationships of the KM variables to the perceived value of ERM are not identified because of the low performance of the models describing these relationships. The analysis reveals important insights into the potential KM support to RM such as: the better adoption of KM people and technology actions, the better the perceived quality of risk control. Equally, the results suggest that the quality of risk control and the benefits of ERM follow different patterns given that there is no correlation between both concepts and the distinct influence of the KM variables in each concept. The ERM scenario is different from that of risk control because ERM, as an answer to RM failures and adaptation to new regulation in financial institutions, has led organizations to adopt new processes, technologies, and governance models. Thus, the search for factors influencing the perceived value of ERM implementation needs additional analysis because what is improved in RM processes individually is not having the same effect on the perceived value of ERM. Based on these model results and the literature review the basis of the ERKMAS (Enterprise Risk Knowledge Management System) is presented.

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Construction projects are risky. However, the characteristics of the risk highly depend on the type of procurement being adopted for managing the project. A build-operate-transfer (BOT) project is recognized as one of the most risky project schemes. There are instances of project failure where a BOT scheme was employed. Ineffective rts are increasingly being managed using various risk management tools and techniques. However, application of those tools depends on the nature of the project, organization's policy, project management strategy, risk attitude of the project team members, and availability of the resources. Understanding of the contents and contexts of BOT projects, together with a thorough understanding of risk management tools and techniques, helps select processes of risk management for effective project implementation in a BOT scheme. This paper studies application of risk management tools and techniques in BOT projects through reviews of relevant literatures and develops a model for selecting risk management process for BOT projects. The application to BOT projects is considered from the viewpoints of the major project participants. Discussion is also made with regard to political risks. This study would contribute to the establishment of a framework for systematic risk management in BOT projects.

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A phenomenon common to almost all fields is that there is a gap between theory and practical implementation. However, this is a particular problem in knowledge management, where much of the literature consists of general principles written in the context of a ‘knowledge world’ that has few, if any, references to how to carry out knowledge management in organisations. In this chapter, we put forward the view that the best way to bridge this gap between general principles and the specific issues facing a given organisation is to link knowledge management to the organisation’s business processes. After briefly reviewing, and rejecting alternative ways in which this gap might be bridged, the chapter goes on to explain the justification for, and the potential benefits and snags of, linking knowledge management to business processes. Successful and unsuccessful examples are presented. We concentrate especially on the issues of establishing what knowledge is relevant to an organisation at present, the need for organisational learning to cope with the inevitable change, and the additional problems posed by the growing internationalisation of operations. We conclude that linking knowledge management in terms of business processes is the best route for organisations to follow, but that it is not the answer to all knowledge management problems, especially where different cultures and/or cultural change are involved.

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Purpose – The purpose of this paper is to examine the state of knowledge management (KM) in the energy sector and more broadly, and consider future directions for research and practice. Design/methodology/approach – The paper reviews the literature on KM and the practice of KM as relevant to the energy sector. Findings – There are many examples of good practice in KM in the sector, and some organisations, especially in the oil industry, are seen as leaders in KM practice. However, other organisations have yet to embark on explicit KM initiatives or projects at all. In addition, some parts of the energy sector discuss KM without any reference to the more general KM literature. Originality/value – Although some parts of the energy sector have justifiably earned a good reputation for KM, other parts are completely unaware of the field, as is apparent from the literature. This review helps to raise awareness and guide future work.