828 resultados para agent oriented approach
Resumo:
It is a big challenge to clearly identify the boundary between positive and negative streams. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on RCV1, and substantial experiments show that the proposed approach achieves encouraging performance.
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Assessment for Learning (AfL) is a title given to classroom evaluative practices that share the purpose of diagnosing and informing teachers and students about learning progress, during the learning process. These practices also have the potential to develop learner autonomy by increasing student motivation and mastery through developing the learner's capacity to monitor and plan his or her own learning progress. Yet teacher adoption of the practices is not a straightforward implementation of techniques within an existing classroom repertoire. Recent research highlights a more complex interrelationship between teacher and student beliefs, identities, and traditions of power within assessment and learning in classroom contexts. These often hidden relationships can add layers of complexity for teachers implementing assessment change, and may act as barriers that frustrate efforts to realise the AfL goal of learner autonomy. By interpreting AfL practices from a sociocultural perspective, the social and cultural contexts that influence classroom assessment can be better understood. In turn teachers can thus be better supported in adopting AfL practices within the complexities of the social, cultural and policy contexts of schooling.
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An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).
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This research applies an archaeological lens to an inner-city master planned development in order to investigate the tension between the design of space and the use of space. The chosen case study for this thesis is Kelvin Grove Urban Village (KGUV), located in inner city Brisbane, Australia. The site of this urban village has strong links to the past. KGUV draws on both the history of the place in particular along with more general mythologies of village life in its design and subsequent marketing approaches. The design and marketing approach depends upon notions of an imagined past where life in a place shaped like a traditional village was better and more socially sustainable than modern urban spaces. The appropriation of this urban village concept has been criticised as a shallow marketing ploy. The translation and applicability of the urban village model across time and space is therefore contentious. KGUV was considered both in terms of its design and marketing and in terms of a reading of the actual use of this master planned place. Central to this analysis is the figure of the boundary and related themes of social heterogeneity, inclusion and exclusion. The refraction of history in the site is also an important theme. An interpretive archaeological approach was used overall as a novel method to derive this analysis.
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Reflection Questions • How does the collaborative reading workshop approach engage students in higher order thinking and deep engagement with text? • How does the collaborative reading workshop approach support students to be active citizens and critically literate? • How does the interaction and collaborative thinking in this approach contribute to the students’ intellectual engagement and the teacher’s pedagogical rigor? • How could this approach be implemented or adapted at your school?
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Many cities around the globe are now considering tourism facilities and their remarkable revenues in order to become competitive in the global economy. In many of these cities a great emphasis is given to the cultural tourism as it plays an important role in the establishment of creative and knowledge-base of cities. The literature points out the importance of local community support in cultural tourism. In such context, the use of new approach and technologies in tourism planning in order to increase the community participation and competitiveness of cities’ cultural assets gains a great significance. This paper advocates a new planning approach for tourism planning, particularly for cultural tourism, to increase the competitiveness of cities. As part of this new approach, the paper introduces the joined up planning approach integrated with a collaborative decision support system: ‘the community-oriented decision support system’. This collaborative planning support system is an effective and efficient tool for cultural tourism planning, which provides a platform for local communities’ participation in the development decision process.
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In recent years, cities show increasing signs of environmental problems due to the negative impacts of urban activities. The degradation and depletion of natural resources, climate change and development pressure on green areas have become major concerns for cities. In response to these problems, urban planning policies have shifted to a sustainable focus and authorities have begun to develop new strategies for improving the quality of urban ecosystems. An extremely important function of an urban ecosystem is to provide healthy and sustainable environments for both natural systems and communities. Therefore, ecological planning is a functional requirement in the establishment of sustainable built environment. With ecological planning human needs are supplied while natural resources are used in the most effective and sustainable manner. And the maintenance of ecological balance is sustained. Protecting human and environmental health, having healthy ecosystems, reducing environmental pollution and providing green spaces are just a few of the many benefits of ecological planning. In this context, the paper briefly presents a short overview of the importance of the implementation of ecological planning into sustainable urban development. Furthermore, the paper defines the conceptual framework of a new method for developing sustainable urban ecosystems through ecological planning approach. In the future of the research, this model will be developed as a guideline for the assessment of the ecological sustainability in built environments.
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Nonlinearity, uncertainty and subjectivity are the three predominant characteristics of contractors prequalification which cause the process more of an art than a scientific evaluation. A fuzzy neural network (FNN) model, amalgamating both the fuzzy set and neural network theories, has been developed aiming to improve the objectiveness of contractor prequalification. Through the FNN theory, the fuzzy rules as used by the prequalifiers can be identified and the corresponding membership functions can be transformed. Eighty-five cases with detailed decision criteria and rules for prequalifying Hong Kong civil engineering contractors were collected. These cases were used for training (calibrating) and testing the FNN model. The performance of the FNN model was compared with the original results produced by the prequalifiers and those generated by the general feedforward neural network (GFNN, i.e. a crisp neural network) approach. Contractor’s ranking orders, the model efficiency (R2) and the mean absolute percentage error (MAPE) were examined during the testing phase. These results indicate the applicability of the neural network approach for contractor prequalification and the benefits of the FNN model over the GFNN model. The FNN is a practical approach for modelling contractor prequalification.
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We argue that web service discovery technology should help the user navigate a complex problem space by providing suggestions for services which they may not be able to formulate themselves as (s)he lacks the epistemic resources to do so. Free text documents in service environments provide an untapped source of information for augmenting the epistemic state of the user and hence their ability to search effectively for services. A quantitative approach to semantic knowledge representation is adopted in the form of semantic space models computed from these free text documents. Knowledge of the user’s agenda is promoted by associational inferences computed from the semantic space. The inferences are suggestive and aim to promote human abductive reasoning to guide the user from fuzzy search goals into a better understanding of the problem space surrounding the given agenda. Experimental results are discussed based on a complex and realistic planning activity.
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Intuitively, any `bag of words' approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies have been mixed or inconclusive. To improve the situation, this paper shows how the natural language properties of the target documents can be used to transform and enrich the term dependencies to more useful statistics. This is done in three steps. The term co-occurrence statistics of queries and documents are each represented by a Markov chain. The paper proves that such a chain is ergodic, and therefore its asymptotic behavior is unique, stationary, and independent of the initial state. Next, the stationary distribution is taken to model queries and documents, rather than their initial distri- butions. Finally, ranking is achieved following the customary language modeling paradigm. The main contribution of this paper is to argue why the asymptotic behavior of the document model is a better representation then just the document's initial distribution. A secondary contribution is to investigate the practical application of this representation in case the queries become increasingly verbose. In the experiments (based on Lemur's search engine substrate) the default query model was replaced by the stable distribution of the query. Just modeling the query this way already resulted in significant improvements over a standard language model baseline. The results were on a par or better than more sophisticated algorithms that use fine-tuned parameters or extensive training. Moreover, the more verbose the query, the more effective the approach seems to become.
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This paper proposes a novel Hybrid Clustering approach for XML documents (HCX) that first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. The empirical analysis reveals that the proposed method is scalable and accurate.
Resumo:
XML document clustering is essential for many document handling applications such as information storage, retrieval, integration and transformation. An XML clustering algorithm should process both the structural and the content information of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. This paper introduces a novel approach that first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. The proposed method reduces the high dimensionality of input data by using only the structure-constrained content. The empirical analysis reveals that the proposed method can effectively cluster even very large XML datasets and outperform other existing methods.
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The New Zealand green lipped mussel preparation Lyprinol is available without a prescription from a supermarket, pharmacy or Web. The Food and Drug Administration have recently warned Lyprinol USA about their extravagant anti-inflammatory claims for Lyprinol appearing on the web. These claims are put to thorough review. Lyprinol does have anti-inflammatory mechanisms, and has anti-inflammatory effects in some animal models of inflammation. Lyprinol may have benefits in dogs with arthritis. There are design problems with the clinical trials of Lyprinol in humans as an anti-inflammatory agent in osteoarthritis and rheumatoid arthritis, making it difficult to give a definite answer to how effective Lyprinol is in these conditions, but any benefit is small. Lyprinol also has a small benefit in atopic allergy. As anti-inflammatory agents, there is little to choose between Lyprinol and fish oil. No adverse effects have been reported with Lyprinol. Thus, although it is difficult to conclude whether Lyprinol does much good, it can be concluded that Lyprinol probably does no major harm.
Resumo:
A number of studies in relation to the place, impact and purpose of Wellness curricula provide insight into the perceived benefits of Wellness education in university environments. Of particular note is the recommendation by many authors that curriculum design fosters personal experiences, reflective practice and active self-managed learning approaches in order to legitimise (give permission for) the adoption of wellness as a personal lifestyle approach in the frenetic pace of student life. From a broader educational perspective, Wellness education provides opportunities for students to engage in learning self regulation skills both within and beyond the context of the Wellness construct.To realise the suggested potential of Wellness education in higher learning, it is necessary that curricula overlay the principles from the domains of both self-regulation and Wellness, to highlight authentic learning as a means to lifelong approaches. Currently, however, systematic development and empirical examination of the Wellness construct have received limited academic investigation. Despite having a multitude of intended purposes from the educative to the therapy oriented goals of the original authors, most wellness models appear to be limited to the “what” of Wellness. Investigations of the “how” and “why” aspects of Wellness may serve to enhance currently existing models by incorporating behaviour modification and learning approaches in order to create more comprehensive frameworks for health education and promotion.It is also important to note that none of the current Wellness models actually address the educative framework necessary for an individual to learn and thus become aware or understand and make choices about their own Wellness.The literature reviewed within this paper would suggest that learner success is optimised by giving learners authentic opportunities to develop and practice self regulation strategies. Such opportunities include learning experiences that: provide options for self determined outcomes; require skills development; recognise principles of successful learning as outlined by the APA; and are scaffolded according to learner needs rather than in generic ways. Thus, configuring a learner centred curriculum in Wellness Education would potentially benefit from overlaying principles from the domains of both SRL and Wellness to highlight authentic learning as a means to lifelong approaches, triggered by undergraduate experiences.Student perceptions are a rich and significant data base for the measurement of their experiences, activities, practices and behaviours. Wellness undergraduate education, such as the “Fitness, Health and Wellness” unit offered by Queensland University of Technology, offers a context in which to confirm possibilities suggested by the literature reviewed in this paper in a practical, Australian context.
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As organisations strive to improve their capabilities in the areas of Service Management and Service-oriented Architectures (SOA), SOA Governance is becoming an increasingly important success factor. However, the concept of SOA Governance is complex and not well-understood, and the adoption of an adequate SOA Governance approach in an organisation can be difficult. Tools that support SOA Governance mostly have a technical bias and rarely address organisational aspects. In this paper, we contribute to the field by specifying a conceptual meta model for SOA Governance that integrates the structure of major IT and SOA Governance frameworks into one consolidated view. By presenting this conceptualisation and a corresponding prototypical implementation of a tool that supports SOA Governance maturity assessment, reference framework exploration and company-specific tailoring of SOA Governance, we provide insights into the first step of a Design Science research project, i.e. the development of an important IT artefact.