Spelling suggestions: "subject:administracióńn+data"
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On sliced methods in dimension reductionLi, Yingxing., 李迎星. January 2005 (has links)
published_or_final_version / abstract / Statistics and Actuarial Science / Master / Master of Philosophy
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Mining frequent itemsets and order preserving submatrices from uncertain dataChui, Chun-kit, 崔俊傑 January 2007 (has links)
published_or_final_version / abstract / Computer Science / Master / Master of Philosophy
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Security in association rule miningWong, Wai-kit, 王偉傑 January 2007 (has links)
published_or_final_version / abstract / Computer Science / Master / Master of Philosophy
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Text subspace clustering with feature weighting and ontologiesJing, Liping., 景麗萍. January 2007 (has links)
published_or_final_version / abstract / Mathematics / Doctoral / Doctor of Philosophy
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The complexities of tracking quantiles and frequent items in a data streamHung, Yee-shing, Regant., 洪宜成. January 2009 (has links)
published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy
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The validity of the use of automated evaluation systems as architectural design aids李少彬, Li, Siu-pan. January 2000 (has links)
published_or_final_version / Architecture / Doctoral / Doctor of Philosophy
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Literature review: implementation of electronic medical records what factors are driving it?Vu, Manh Tuan. January 2009 (has links)
published_or_final_version / Public Health / Master / Master of Public Health
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Developable surfaces: flattening methods and applications顔文川, Gan, Man-chuen, Abel. January 1995 (has links)
published_or_final_version / Mechanical Engineering / Master / Master of Philosophy
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Automatic data integration with generalized mapping definitionsTian, Aibo 18 September 2014 (has links)
Data integration systems provide uniform access to a set of heterogeneous structured data sources. An essential component of a data integration system is the mapping between the federated data model and each data source. The scale of interconnect among data sources in the big data era is a new impetus for automating the mapping process. Despite decades of research on data integration, generating mappings still requires extensive labor. The thesis of this research is that the progress on automatic data integration has been limited by a narrow definition of mapping. The common mapping process is to find correspondences between pairs of entities in the data models, and create logic expressions over the correspondences as executable mappings. This does not cover all issues in real world applications. This research aims to overcome this problem in two ways: (1) generalize the common mapping definition for relational databases; (2) address the problem in a more general framework, the Semantic Web. The Semantic Web provides flexible graph based data models and reasoning capabilities as in knowledge representation systems. The new graph data model introduces opportunities for new mapping definitions. The comparison of mapping definitions and solutions for both relational databases and the Semantic Web is discussed. In this dissertation, I propose two generalizations of mapping problems. First, the common schema matching definition for relational databases is generalized from finding correspondences between pairs of attributes to finding correspondences consisting of relations, attributes, and data values. This generalization solves real world issues that are not previously covered. The same generalization can be applied to ontology matching in the Semantic Web. The second piece of work generalizes the ontology mapping definition from finding correspondences between pairs of entities to pairs of graph paths (sequences of entities). As a path provides more context than a single entity, mapping between paths can solve two challenges in data integration: the missing mapping challenge and the ambiguous mapping challenge. Combining the two proposed generalizations together, I demonstrate a complete data integration system using the Semantic Web techniques. The complete system includes the components of automatic ontology mapping and query reformulation, and semi-automatically federates the query results from multiple data sources. / text
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Privacy-aware publication and utilization of healthcare dataPark, Yubin 28 October 2014 (has links)
Open access to health data can bring enormous social and economical benefits. However, such access can also lead to privacy breaches, which may result in discrimination in insurance and employment markets. Privacy is a subjective and contextual concept, thus it should be interpreted from both systemic and information perspectives to clearly understand potential breaches and consequences. This dissertation investigates three popular use cases of healthcare data: specifically, 1) synthetic data publication, 2) aggregate data utilization, and 3) privacy-aware API implementation. For each case, we develop statistical models that improve the privacy-utility Pareto frontier by leveraging a variety of machine learning techniques such as information theoretic privacy measures, Bayesian graphical models, non-parametric modeling, and low-rank factorization techniques. It shows that much utility can be extracted from health records while maintaining strong privacy guarantees and protection of sensitive health information. / text
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