Thesis (doctoral)--Université de Neuchâtel, 1991. / Includes bibliographical references (p. 112) and index.

Ko Hon Man. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 68-72). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background and Motivation --- p.1 / Chapter 1.2 --- Thesis Organization --- p.4 / Chapter 2 --- Related Work --- p.6 / Chapter 2.1 --- Semi-supervised learning --- p.6 / Chapter 2.2 --- Hierarchical Categorization --- p.10 / Chapter 3 --- Framework Overview --- p.13 / Chapter 4 --- Inherent Concept Detection --- p.18 / Chapter 4.1 --- Data Preprocessing --- p.18 / Chapter 4.2 --- Concept Detection Algorithm --- p.22 / Chapter 4.3 --- Kernel-based Distance Measure --- p.27 / Chapter 5 --- Training Example Discovery from Unlabeled Documents --- p.33 / Chapter 5.1 --- Training Document Discovery --- p.33 / Chapter 5.2 --- Automatically determining the number of extracted positive examples --- p.37 / Chapter 5.3 --- Classification Model --- p.39 / Chapter 6 --- Experimental Evaluation --- p.44 / Chapter 6.1 --- Corpus Description --- p.44 / Chapter 6.2 --- Evaluation Metric --- p.49 / Chapter 6.3 --- Result Analysis --- p.50 / Chapter 7 --- Conclusions and Future Work --- p.66 / Bibliography --- p.68 / Chapter A --- Detailed result on the inherent concept detection process for the TDT and RCV1 corpora --- p.73

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: Vijay K. Shanker, Dept. of Computer & Information Sciences. Includes bibliographical references.

Thesis (M. Phil.)--University of Hong Kong, 1989.

published_or_final_version / Electrical Engineering / Master / Master of Philosophy

This thesis presents an approach for supporting the information access requirements of engineering designers. Technical and cultural factors are increasing the quantity of information that is available to designers. As a consequence, they require improved tools not just to retrieve this information but also to allow it to be organised and classified into meaningful structures to assist in its management. The research has been undertaken from two interrelated standpoints. The first focused on empirical studies of the information access requirements of practising designers. The second concerned the development, based on the key findings from the initial studies, of classification structures for aerospace design information and their incorporation in a computer-based information system. The empirical studies of designers were carried out in two separate stages. The first involved the characterisation of the information usage of a range of engineering designers with different backgrounds. The results indicated important differences in the usage and storage of information between designers. The second study examined documents used by practising designers. From this, a number of core classification scheme types were identified that allow information to be organised from a variety of user perspectives. The results of the empirical studies informed the development of a novel information system based on a combination of. (i) faceted-like, automatic, non-mutually exclusive classification principles and (ii) a hybrid browsing approach that `prunes' the browsable classification scheme, according to concept selections made by the user. The system overcomes some of the usual problems of browsing classification structures and allows the inference of linked relationships between different classification categories. This represents a powerful feature that is beyond the capabilities of existing search approaches. The benefits of the system, when applied to a number of typical engineering information search scenarios, are discussed followed by an evaluation of the approach. Finally, a number of conclusions and suggestions for future research are suggested.

Thesis (Ph.D.)--University of Western Australia, 2007.

Thesis (Ph. D.)--University of Alberta, 2009. / Title from PDF file main screen (viewed on Oct. 20, 2009). "A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosophy, Department of Electrical and Computer Engineering, University of Alberta." Includes bibliographical references.

This thesis compares different methods that could be used to construct a computer aided diagnosis (CAD) system that analyzes mammograms. Such systems have many steps, but this thesis focuses on feature extraction, feature selection, and classification. The main comparison is between the simplified Rubber Band Straightening Transform (SRBST) and the Onion Transform, which are used to extract texture features. Another comparison is between 2D and 3D co-occurrence matrices. Next, features are selected using a greedy algorithm. This section mainly compares the effectiveness of Receiver Operating Characteristic (ROC) and Class Overlap Rating (COR). Also evaluated are the effectiveness of Linear Discriminate Analysis (LDA) and the sort order of features. Then the selected features are used to classify the lesions. In this part, Nearest Mean, Nearest Neighbor, and Maximum Likelihood are compared. The results are then used to determine the best combination of methods to use in a CAD system.

As recentes tecnologias de desenvolvimento e distribuição de componentes possibilitaram o aumento do número de componentes disponíveis no mercado. No entanto, eles muitas vezes estão dispersos e não publicados adequadamente para a comunidade de pesquisa e desenvolvimento de software. Encontrar componentes apropriados para solucionar um problema particular não é uma tarefa simples e novas técnicas devem ser desenvolvidas para o reuso efetivo de componentes. Um dos maiores desafios em reusar componentes consiste em classificá-los corretamente para futuras consultas. Classificar componentes para possibilitar uma busca eficaz depende da qualidade das informações adquiridas, que viabilizam melhor precisão e cobertura das consultas ao encontrar componentes reutilizáveis em potencial. Ao mesmo tempo, mecanismos de classificação e busca devem ser fáceis o suficiente para convencer os desenvolvedores a reusar componentes. Este trabalho estuda as técnicas de classificação de componentes de software, repositórios e métodos de busca. é apresentada uma proposta de modelo de classificação de componentes que considera não apenas sua função, mas o negócio onde ele está inserido e seus atributos de qualidade. Um método de preenchimento semi-automático das informações é proposto, de modo a diminuir os custos de classificação. O protótipo REUSE+ foi construído para exemplificar o uso do modelo e do método de classificação semi-automática, de forma a validar a proposta, destacando, por fim, as principais contribuições do trabalho. / The recent developments on components technologies have increased the number of components available to the market. These components are, however, distributed overall the world and not properly advertised to the research and development communities. Finding the appropriate components to solve a particular problem is not very straightforward and new techniques must be developed to effectively reuse components. One of the great challenges in reusing components is concerned with how to actually classify components \"properly\" in order to further retrieve them. Classifying components for effective retrieval depends on acquiring the appropriate information in classification to improve the precision and recall rates in retrieval; finding only the potentially reusable components and not missing potential solutions. At the same time, the classification and retrieval mechanisms must be easy enough to persuade developers to reuse components. This work studies the classification techniques of software components, repository and retrieval methods. Hereafter is presented a proposal of components classification model that considers not just its function, but business and quality attributes. It is proposed a semi-automatic classification mechanism of software information, allowing a cheaper classification. REUSE+ prototype was built to exemplify the use of model and method of semi-automatic classification, allowing the described proposal validation, highlighting at the end the mainly contributions of the work.