Modellgetriebene Entwicklung inhaltsbasierter Bildretrieval-Systeme auf der Basis von objektrelationalen Datenbank-Management-Systeme

In this thesis, the model-driven software development paradigm is employed in order to support the development of Content-based Image Retrieval Systems (CBIRS) for different application domains. Modeling techniques, based on an adaptable conceptual framework model, are proposed for deriving the components of a concrete CBIRS. Transformation techniques are defined to automatically implement the derived application specific models in an object-relational database management system. A set of criteria assuring the quality of the transformation are derived from the theory for preserving information capacity applied in database design.In dieser Dissertation wird das Paradigma des modellgetriebenen Softwareentwurfs für die Erstellung von inhaltsbasierten Bildretrieval-Systemen verwendet. Ein adaptierbares Frameworkmodell wird für die Ableitung des Modells eines konkreten Bildretrieval-Systems eingesetzt. Transformationstechniken für die automatische Generierung von Implementierungen in Objektorientierten Datenbank-Management-Systemen aus dem konzeptuellen Modell werden erarbeitet. Die aus der Theorie des Datenbankentwurfs bekannten Anforderungen zur Kapazitätserhaltung der Transformation werden verwendet, um Kriterien für die erforderliche Qualität der Transformation zu definieren

Guidelines for representing complex cardinality constraints in binary and ternary relationships

Ternary relationships represent the association among three entities whose constraints database designers do not always know how to manage. In other words, it is very difficult for the designer to detect, represent and add constraints in a ternary relationship according to the domain requirements. To remedy the shortcomings in capturing the semantics required for the representation of this kind of relationship, the present paper discusses a practical method to motivate the designer's use of ternary relationships in a methodological framework. The method shows how to calculate cardinality constraints in binary and ternary relationships and to preserve the associated semantics until the implementation phase of the database development method.This work forms part of the ‘Thuban: Natural Interaction Platform for Virtual Attending in Real Environments’ project (TIN2008-02711), the Spanish Ministry of Industry, Tourism and Trade through the project Semants (TSI-020100-2009-419) and also by the Spanish research projects: MA2VICMR: Improving the access, analysis and visibility of the multilingual and multimedia information in web for the Region of Madrid (S2009/TIC-1542).Publicad

Interim research assessment 2003-2005 - Computer Science

This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities

Data Management for Dynamic Multimedia Analytics and Retrieval

Multimedia data in its various manifestations poses a unique challenge from a data storage and data management perspective, especially if search, analysis and analytics in large data corpora is considered. The inherently unstructured nature of the data itself and the curse of dimensionality that afflicts the representations we typically work with in its stead are cause for a broad range of issues that require sophisticated solutions at different levels. This has given rise to a huge corpus of research that puts focus on techniques that allow for effective and efficient multimedia search and exploration. Many of these contributions have led to an array of purpose-built, multimedia search systems. However, recent progress in multimedia analytics and interactive multimedia retrieval, has demonstrated that several of the assumptions usually made for such multimedia search workloads do not hold once a session has a human user in the loop. Firstly, many of the required query operations cannot be expressed by mere similarity search and since the concrete requirement cannot always be anticipated, one needs a flexible and adaptable data management and query framework. Secondly, the widespread notion of staticity of data collections does not hold if one considers analytics workloads, whose purpose is to produce and store new insights and information. And finally, it is impossible even for an expert user to specify exactly how a data management system should produce and arrive at the desired outcomes of the potentially many different queries. Guided by these shortcomings and motivated by the fact that similar questions have once been answered for structured data in classical database research, this Thesis presents three contributions that seek to mitigate the aforementioned issues. We present a query model that generalises the notion of proximity-based query operations and formalises the connection between those queries and high-dimensional indexing. We complement this by a cost-model that makes the often implicit trade-off between query execution speed and results quality transparent to the system and the user. And we describe a model for the transactional and durable maintenance of high-dimensional index structures. All contributions are implemented in the open-source multimedia database system Cottontail DB, on top of which we present an evaluation that demonstrates the effectiveness of the proposed models. We conclude by discussing avenues for future research in the quest for converging the fields of databases on the one hand and (interactive) multimedia retrieval and analytics on the other

Efficient similarity-based operations for data integration

Similarity-based operations, similarity join, similarity grouping, data integrationMagdeburg, Univ., Fak. für Informatik, Diss., 2004von Eike Schalleh

Handling default data under a case-based reasoning approach

The knowledge acquired through past experiences is of the most importance when humans or machines try to find solutions for new problems based on past ones, which makes the core of any Case-based Reasoning approach to problem solving. On the other hand, existent CBR systems are neither complete nor adaptable to specific domains. Indeed, the effort to adapt either the reasoning process or the knowledge representation mechanism to a new problem is too high, i.e., it is extremely difficult to adapt the input to the computational framework in order to get a solution to a particular problem. This is the drawback that is addressed in this work.This work is funded by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within projects PEst-OE/EEI/UI0752/2014 and PEst-OE/QUI/UI0619/2012