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Formalized modeling of qualitative case studies

Auteur(s)
Maison d'édition
Neuchâtel
Date de parution
2013
Mots-clés
Résumé
This thesis aims to solve the problems of data modelization and processing emerging in qualitative case studies. Established on grounded theory, a comprehensive method is proposed, initially elaborated in the form of a workflow solution. A suit of ontologies are proposed serving for knowledge representation, integration, and extraction. Based on this knowledge, topic analysis is conducted to discover the latent information out of the original documents in order to depict the implicit themes and set up sophisticated hierarchical structures of these topics. With the built structures, ontology inference is carried out to produce new facts to assist domain tasks. This method is applicable within the range of multiple lingualism including non-alphabetical languages such as Chinese. Experiments tested on the implemented tool demonstrate that the proposed method offers satisfactory results compared with existing methods. The overall thesis provides a novel and complete solution to profoundly study and analyze case study text with a qualitative method. It brings a series of benefits to a couple of domains which share similar essence from the point of view of data processing.
Notes
, Université de Neuchâtel
URI
Autre version
http://doc.rero.ch/record/210251
Type de publication
Resource Types::text::thesis::doctoral thesis