On Real-time Top k Querying for Mobile Services

Mobile services offering multi-feature query capabilities must meet tough response time requirements to gain customer acceptance. The top-k query model is a popular candidate to implement such services. Focusing on a central server architecture we present a new algorithm called SR-Combine that closely self-adapts itself to particular cost ratios in such environments. SR-Combine optimizes both the object accesses and the query run-times. We perform a series of synthetical benchmarks to verify the superiority of SR-Combine over existing algorithms. In order to assess whether it can meet the stated response time requirements for mobile access, we propose a psychologically founded model. It turns out that for a wide range of practical cases SR-Combine can satisfy these goals. Where this isn't yet the case, we show up ways how to get there systematically. Thus with SR-Combine a breakthrough in real-time capabilities of top-k querying for mobile services is in sight now

An XML-based Multimedia Middleware for Mobile Online Auctions

Pervasive Internet services today promise to provide users with a quick and convenient access to a variety of commercial applications. However, due to unsuitable architectures and poor performance user acceptance is still low. To be a major success mobile services have to provide device-adapted content and advanced value-added Web services. Innovative enabling technologies like XML and wireless communication may for the first time provide a facility to interact with online applications anytime anywhere. We present a prototype implementing an efficient multimedia middleware approach towards ubiquitous value-added services using an auction house as a sample application. Advanced multi-feature retrieval technologies are combined with enhanced content delivery to show the impact of modern enterprise information systems on today’s e-commerce applications

Evaluation of a hierarchical taxonomy preparation method for document classification

El objetivo del proyecto es la creación de una taxonomía jerárquica de forma automática para la categorización de textos matemáticos haciendo uso de coclustering basado en el algoritmo "Consistent Bipartite Spectral Graph Copartitioning". Una vez creada la taxonomía habrá que evaluar sus prestaciones analizando los resultados con datos reales pertenecientes a una biblioteca digital matemátic