89 resultados para Knowledge discovery in databases


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This chapter introduces the latest practices and technologies in the interactive interpretation of environmental data. With environmental data becoming ever larger, more diverse and more complex, there is a need for a new generation of tools that provides new capabilities over and above those of the standard workhorses of science. These new tools aid the scientist in discovering interesting new features (and also problems) in large datasets by allowing the data to be explored interactively using simple, intuitive graphical tools. In this way, new discoveries are made that are commonly missed by automated batch data processing. This chapter discusses the characteristics of environmental science data, common current practice in data analysis and the supporting tools and infrastructure. New approaches are introduced and illustrated from the points of view of both the end user and the underlying technology. We conclude by speculating as to future developments in the field and what must be achieved to fulfil this vision.

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Purpose – The construction industry is a very important part of the Malaysian economy. The government's aim is to make the industry more productive, efficient and safe. Small to medium-sized enterprises (SMEs) are at the core of the Malaysian construction industry and account for about 90 per cent of companies undertaking construction work. One of the main challenges faced by the Malaysian construction industry is the ability to absorb new knowledge and technology and to implement it in the construction phase. The purpose of this paper is to consider absorptive capacity in Malaysian construction SMEs in rural areas. Design/methodology/approach – The research was conducted in three stages: first, understanding the Malaysian construction industry; second, a literature review on the issues related to absorptive capacity and discussions with the Construction Industry Development Board (CIDB); and third, multiple case studies in five construction SMEs operating in a rural area to validate the factors influencing absorptive capacity. Findings – Nine key factors were identified influencing absorptive capacity in Malaysian construction SMEs operating in rural areas. These factors involved: cost and affordability; availability and supply; demand; infrastructure; policies and regulations; labour readiness; workforce attitude and motivation; communication and sources of new knowledge and; culture. Originality/value – The key factors influencing absorptive capacity presented in this paper are based on validation from the case studies in five construction SMEs in Malaysia. The research focuses on how they operate in rural areas; however, the research results have wider application than just Malaysia. The key factors identified as influencing absorptive capacity can serve as a basis for considering knowledge absorption in the wider context by SMEs in other developing countries.

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This paper explores the social and cultural knowledge embedded in the textbooks for language and literacy education in a Chinese heritage language school, the Zhonguo School, in Montreal, Quebec, Canada. It examines how Chinese language arts textbooks introduce the child reader to cultural knowledge considered legitimate and valued in China as well as in Chinese diasporan communities. Furthermore, it looks at the construction of cultural knowledge in Chinese language textbooks in relation to the mainstream ideology to which immigrant children are exposed in and out of mainstream school classrooms. It looks at how the power relationship between legitimate cultural knowledge in majority and minority contexts is established and to what extent it affects language minority students' literacy practices in mainstream school and heritage language school contexts. Data sources are the Chinese textbooks used from kindergarten to Grade 5 in a Chinese heritage language school.

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So-called ‘radical’ and ‘critical’ pedagogy seems to be everywhere these days on the landscapes of geographical teaching praxis and theory. Part of the remit of radical/critical pedagogy involves a de-centring of the traditional ‘banking’ method of pedagogical praxis. Yet, how do we challenge this ‘banking’ model of knowledge transmission in both a large-class setting and around the topic of commodity geographies where the banking model of information transfer still holds sway? This paper presents a theoretically and pedagogically driven argument, as well as a series of practical teaching ‘techniques’ and tools—mind-mapping and group work—designed to promote ‘deep learning’ and a progressive political potential in a first-year large-scale geography course centred around lectures on the Geographies of Consumption and Material Culture. Here students are not only asked to place themselves within and without the academic materials and other media but are urged to make intimate connections between themselves and their own consumptive acts and the commodity networks in which they are enmeshed. Thus, perhaps pedagogy needs to be emplaced firmly within the realms of research practice rather than as simply the transference of research findings.

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Information systems integration becomes critical in enhancing organisational competitiveness through effective use of information resource provided by the whole host of information systems. Information systems integration in its nature is a process of bringing about the capability of communication and information exchange between systems; while interoperability, often as the result of systems integration, is such a capability. However currently there is a lack of theoretical foundation for representation and measure of the interoperability in organisations. Organisational semiotics provides a theoretical foundation for systems interoperability. A notion of ‘semiotic interoperability’ is proposed in this paper as a paradigm, guiding systems integration and measuring degree of interoperability, covering aspects from physical properties, transmission structure of signs, placing emphasis on communicating meaning, intention to social consequence of information.

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It is widely assumed that the British are poorer modern foreign language (MFL) learners than their fellow Europeans. Motivation has often been seen as the main cause of this perceived disparity in language learning success. However, there have also been suggestions that curricular and pedagogical factors may play a part. This article reports a research project investigating how German and English 14- to 16-year-old learners of French as a first foreign language compare to one another in their vocabulary knowledge and in the lexical diversity, accuracy and syntactic complexity of their writing. Students from comparable schools in Germany and England were set two writing tasks which were marked by three French native speakers using standardised criteria aligned to the Common European Framework of Reference (CEF). Receptive vocabulary size and lexical diversity were established by the X_lex test and a verb types measure respectively. Syntactic complexity and formal accuracy were respectively assessed using the mean length of T-units (MLTU) and words/error metrics. Students' and teachers' questionnaires and semi-structured interviews were used to provide information and participants' views on classroom practices, while typical textbooks and feedback samples were analysed to establish differences in materials-related input and feedback in the two countries. The German groups were found to be superior in vocabulary size, and in the accuracy, lexical diversity and overall quality – but not the syntactic complexity – of their writing. The differences in performance outcomes are analysed and discussed with regard to variables related to the educational contexts (e.g. curriculum design and methodology).

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Knowledge recommendation has become a promising method in supporting the clinicians decisions and improving the quality of medical services in the constantly changing clinical environment. However, current medical knowledge management systems cannot understand users requirements accurately and realize personalized recommendation. Therefore this paper proposes an ontological approach based on semiotic principles to personalized medical knowledge recommendations. In particular, healthcare domain knowledge is conceptualized and an ontology-based user profile is built. Furthermore, the personalized recommendation mechanism is illustrated.

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Knowledge management has become a promising method in supporting the clinicians′ decisions and improving the quality of medical services in the constantly changing clinical environment. However, current medical knowledge management systems cannot understand users′ requirements accurately and realize personalized matching. Therefore this paper proposes an ontological approach based on semiotic principles to personalized medical knowledge matching. In particular, healthcare domain knowledge is conceptualized and an ontology-based user profile is built. Furthmore, the personalized matching mechanism and algorithm are illustrated.

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Twitter is both a micro-blogging service and a platform for public conversation. Direct conversation is facilitated in Twitter through the use of @’s (mentions) and replies. While the conversational element of Twitter is of particular interest to the marketing sector, relatively few data-mining studies have focused on this area. We analyse conversations associated with reciprocated mentions that take place in a data-set consisting of approximately 4 million tweets collected over a period of 28 days that contain at least one mention. We ignore tweet content and instead use the mention network structure and its dynamical properties to identify and characterise Twitter conversations between pairs of users and within larger groups. We consider conversational balance, meaning the fraction of content contributed by each party. The goal of this work is to draw out some of the mechanisms driving conversation in Twitter, with the potential aim of developing conversational models.

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Flexibility of information systems (IS) have been studied to improve the adaption in support of the business agility as the set of capabilities to compete more effectively and adapt to rapid changes in market conditions (Glossary of business agility terms, 2003). However, most of work on IS flexibility has been limited to systems architecture, ignoring the analysis of interoperability as a part of flexibility from the requirements. This paper reports a PhD project, which proposes an approach to develop IS with flexibility features, considering some challenges of flexibility in small and medium enterprises (SMEs) such as the lack of interoperability and the agility of their business. The motivation of this research are the high prices of IS in developing countries and the usefulness of organizational semiotics to support the analysis of requirements for IS. (Liu, 2005).

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Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets.

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Human brain imaging techniques, such as Magnetic Resonance Imaging (MRI) or Diffusion Tensor Imaging (DTI), have been established as scientific and diagnostic tools and their adoption is growing in popularity. Statistical methods, machine learning and data mining algorithms have successfully been adopted to extract predictive and descriptive models from neuroimage data. However, the knowledge discovery process typically requires also the adoption of pre-processing, post-processing and visualisation techniques in complex data workflows. Currently, a main problem for the integrated preprocessing and mining of MRI data is the lack of comprehensive platforms able to avoid the manual invocation of preprocessing and mining tools, that yields to an error-prone and inefficient process. In this work we present K-Surfer, a novel plug-in of the Konstanz Information Miner (KNIME) workbench, that automatizes the preprocessing of brain images and leverages the mining capabilities of KNIME in an integrated way. K-Surfer supports the importing, filtering, merging and pre-processing of neuroimage data from FreeSurfer, a tool for human brain MRI feature extraction and interpretation. K-Surfer automatizes the steps for importing FreeSurfer data, reducing time costs, eliminating human errors and enabling the design of complex analytics workflow for neuroimage data by leveraging the rich functionalities available in the KNIME workbench.

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We show how multivariate GARCH models can be used to generate a time-varying “information share” (Hasbrouck, 1995) to represent the changing patterns of price discovery in closely related securities. We find that time-varying information shares can improve credit spread predictions.

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This book introduces six general procedures for teaching grammar to learners of English as a second language. The procedures are designed to encourage learners to notice, explore and practice grammar in context. Each description and discussion of a procedure is followed by two sample lesson plans together with sample texts and worksheets. Teachers can either use these 'as is' or adapt them for their own students. The lessons are suitable for a wide range of students from beginning learners to advanced learners. A final chapter provides examples of lessons in which several procedures are combined. In addition, before each sample lesson plan, the grammar focus of the lesson is briefly explained for the teacher. These procedures all illustrate how grammar can be taught through texts, and they are based on an understanding of the latest research on pedagogical grammar and the role of language awareness and discovery in second language learning and provide teachers with principles they can apply in developing their own teaching materials and activities. The grammar explanations preceding each teaching plan provide a fresh look at English grammar drawing on work in systemic functional linguistics.