No description available.

Thesis (M.C.S.)--Miami University, Dept. of Computer Science and Systems Analysis, 2007. / Title from first page of PDF document. Includes bibliographical references (p. 86-88).

No description available.

Le volume de données disponible croît de manière très importante et ouvre d'importants défis pour les exploiter. Les domaines scientifiques du Web sémantique et des ontologies sont alors une réponse pour aider à traiter les données de manière efficace. Ainsi les ontologies sont actuellement devenues incontournables dans de nombreux domaines d'application pour représenter la connaissance experte.Le domaine que nous considérons dans nos travaux est celui des Interventions Non Médicamenteuses (INM) nommées Non-Pharmacological Interventions (NPIs) en anglais. Elles sont de plus en plus étudiées sur le plan scientifique. Elles sont liées à divers secteurs : psychologie, thérapies manuelles, nutrition, activités sportives adaptées, solutions e-santé, etc.Avec l'augmentation de leur usage, il devient de plus en plus nécessaire d'évaluer leur efficacité de manière scientifique, dans une démarche pilotée par des spécialistes et expliquée de manière claire et accessible aux utilisateurs. Pour ce faire, il est essentiel de disposer d'une classification évolutive et consensuelle effectuée au niveau international pour les spécialistes. Dans ce domaine, le développement d'une ontologie est crucial pour faciliter les recherches bibliographiques et mettre en place des bonnes pratiques.Dans nos travaux, nous nous sommes intéressés à deux enjeux majeurs liés à la construction d'une telle ontologie, d'une part comment effectuer la collecte du vocabulaire et d'autre part comment aider à la compréhension par visualisation.La construction manuelle de l'ontologie est en effet fastidieuse et longue. En particulier, la collecte des termes liés au domaine des INM nécessite beaucoup d'efforts et de temps tant le champ du vocabulaire est large. Ainsi le terme INM lui-même est parfois remplacé par d'autres (médecines alternatives, médecines douces, etc). Une méthode automatique ou semi-automatique est alors vue comme une aide importante pour la construction de la représentation de la connaissance.De plus, les ontologies sont parfois considérées comme difficiles à prendre en main pour les personnes non spécialistes de modélisation, en raison de leur complexité, de leur taille ou des propriétés et relations qu'elles incluent. Ainsi, un outil de visualisation doit être proposé pour les experts des INM. L'outil aura deux buts, d'une part visualiser l'ontologie existante, d'autre part proposer des modifications relatives à la structuration de l'ontologie qui doit se construire de manière collaborative.Des contributions sont proposées dans cette thèse sur ces deux sujets (construction du vocabulaire et visualisation). Deux approches sont présentées pour la construction, l'une reposant sur la connaissance experte et l'autre sur un corpus. Une mesure de similarité est introduite et évaluée. Pour la visualisation, notre proposition repose sur l'utilisation de cartes conceptuelles. Il s'agit alors de ré-écrire l'ontologie sous ce nouveau format et de proposer des outils permettant de distinguer les différents éléments et liens entre les éléments. Un outil a été implémenté, permettant de transformer les ontologies décrites en OWL pour les visualiser. / The explosion of data on the Internet leads to challenges in working with them. Semantic Web and ontology are required to address those problems. Nowadays, ontology plays more and more an important role as a means in domain knowledge representation.In recent years, Non-Pharmacological Interventions (NPIs) have attracted a lot of attention in the health care community. NPIs can no longer stop at a professional discipline to describe them (psychotherapy, manual therapy, dietary supplement, adapted physical activity, e-health solution, etc.). It requires access to a more concrete level of description where each NPI can be evaluated by science, monitored by professionals and explained to the patient. To do this, an international and evolutionary classification based on the results of science is necessary. Thus, developing an ontology for NPIs is crucial. This ontology will facilitate bibliographic research, usage statistics and the identification of good practices.Constructing this ontology manually is time consuming and thus an expensive process. Particularly, the step of collecting the NPI terminology requires much more time than the rest, because of heterogeneous and big resources in the context of NPIs. An automatic or semi-automatic method is thus essential to support NPI experts in this task.Besides, ontologies are often complex with lots of classes, properties and relationships. They are not easy to understand by domain experts. Therefore, a simple and friendly visualization of the ontology for NPI experts needs to be considered. The visualization does not only help NPI experts to easily understand the ontology but also provides support for the NPI ontology development process.In this thesis, we propose methodologies to address the aforementioned challenges. The first contribution concerns the semi-automatic process for collecting NPI terms. Two approaches, knowledge-based and corpus-based, are presented to retrieve candidate NPI terms. A new similarity measure for NPI is proposed and evaluated. The second contribution is a new method for ontology visualization based on MindMap. This work aims at providing a simple and friendly tool to visualize an ontology which is used by domain experts. We propose a MindMap-based notation for ontology visualization by transforming ontology components to MindMap elements. A web-based tool is then implemented to convert OWL ontologies to FreeMind documents which can be imported by existing Mind-Mapping applications to make visualizations.

Background: A large number of life science ontologies has been developed to support different application scenarios such as gene annotation or functional analysis. The continuous accumulation of new insights and knowledge affects specific portions in ontologies and thus leads to their adaptation. Therefore, it is valuable to study which ontology parts have been extensively modified or remained unchanged. Users can monitor the evolution of an ontology to improve its further development or apply the knowledge in their applications.

Information visualization can be valuable in a wide range of applications, it deals with abstract, non-spatial data and with the representation of data elements in a meaningful form irrespective of the size of the data, because sometimes visualization itself focuses on the certain key aspects of the data in the representation and thus it helps by providing ease for the goal oriented interpretation. Information visualization focuses on providing a spontaneous and deeper level of the understanding of the data. Research collaboration enhances sharing knowledge and also enhances an individual’s talent. New ideas are generated when knowledge is shared and transferred among each other. According to (He et al, 2009) Research collaboration has been considered as a phenomenon of growing importance for the researchers, also it should be encouraged and is considered to be a “good thing” among the researchers. The main purpose of this thesis work is to prepare a model for the competence profile visualization purpose. For this purpose the study of different visualization techniques that exist in the field of information visualization are discussed in this thesis work. The study and discussion about the visualization techniques motivates in selecting appropriate visualization techniques for the visualization of Ontology-based competence profiles for research collaboration purpose. A proof of concept is developed which shows how these visualization techniques are applied to visualize several components of competence profile.

For ontology development, sharing and usage, availability of a suitable visualization method is essential. Much research has been done in this area, but an ideal method is still missing. One of the reasons might be that most of the available tools offer a general visualization but various use cases require specific approaches to the visualization. This master thesis gives a general overview of current visualization methods and their implementations. Both the methods and specific visualization tools are evaluated from the perspective of several possible use case categories. Special focus is given on visualization of ontology transformations. As none of the available implementations is suitable for this use case as is, an alternative approach is proposed. This approach is based on using several existing visualization implementations together and allowing switching between them using a zoom-like function. It is experimentally implemented as a Protégé plugin.

Thesis (M.C.S.)--Miami University, Dept. of Computer Science and Systems Analysis, 2009. / Title from first page of PDF document. Includes bibliographical references (p. 122-123).

Submitted by TATIANE DOS SANTOS DE FREITAS LOPES null (thaty_lopez@hotmail.com) on 2017-09-26T11:27:52Z No. of bitstreams: 1 Dissertação - Tatiane Lopes.pdf: 3190468 bytes, checksum: 328cfdb2f66173743a997091b892cd2b (MD5) / Approved for entry into archive by Monique Sasaki (sayumi_sasaki@hotmail.com) on 2017-09-28T12:25:17Z (GMT) No. of bitstreams: 1 lopes_tsf_me_mar.pdf: 3190468 bytes, checksum: 328cfdb2f66173743a997091b892cd2b (MD5) / Made available in DSpace on 2017-09-28T12:25:17Z (GMT). No. of bitstreams: 1 lopes_tsf_me_mar.pdf: 3190468 bytes, checksum: 328cfdb2f66173743a997091b892cd2b (MD5) Previous issue date: 2017-08-31 / Um sistema de recuperação de informação é um elemento mediador entre um acervo documental e os usuários que buscam por documentos relevantes. Nesse contexto, as interfaces desempenham uma função importante: em um primeiro momento, auxiliando o usuário na tarefa de expressar a sua necessidade de informação por meio de uma expressão de busca e, em um segundo momento, fornecendo recursos para ajudá-lo a selecionar documentos relevantes dentre os resultados obtidos. A recuperação de informação é um processo linguístico cuja eficiência depende de coincidências terminológicas entre a expressão de busca do usuário e a representação dos documentos. Este trabalho propõe um modelo de interface na qual a estrutura terminológica de uma ontologia é utilizada para auxiliar o usuário na seleção de documentos relevantes dentre aqueles resultantes de sua busca. Caracteriza-se como uma pesquisa de natureza aplicada, e exploratória e bibliográfica quanto aos procedimentos. Conclui-se que a apresentação visual de uma ontologia permite o desenvolvimento de interfaces dinâmicas e interativas, proporcionando ao usuário uma navegação estimulante e prazerosa por entre os documentos resultantes de sua busca, tendo por base os termos de uma determinada área de conhecimento. / An information retrieval system is a mediating element between a document collection and the users who looking for relevant documents. In this context, interfaces play an important role: firstly, assisting the user to expressing their information need by means of a search expression, and secondly by providing resources to help selecting relevant documents from the obtained results. The information retrieval is a linguistic process whose efficiency depends on terminological coincidences between the user’s query and the representation of documents. This work proposes an interface model in which the terminological structure of an ontology is used to assist the user in the selection of relevant documents among those resulting from their search. It is characterized as an applied, exploratory and bibliographic research. It is concluded that the visual presentation of ontology allows the development of dynamic and interactive interfaces, providing the user with stimulating and pleasant navigation among the documents resulting from their search, based on the terms of a certain knowledge area.

Práce se zabývá vizualizací rozdílu mezi dvěma RDF modely. Jsou zde porovnávány existující nástroje a postupy, tyto nástroje jsou rozděleny do dvou kategorií. První kategorie reprezentuje textový přístup k zobrazování ontologií a potažmo jejich rozdílu, druhá zastupuje grafické metody. Na základě jejich zkoumání je navržen nový přístup. Konkrétně se jedná o nástroj, který podporuje paralelní textovou reprezentaci ontologií, která je obohacena o sémantické anotace (delta tags)