Recent Advances in Modularity Optimization and Their Application in Retailing

In this contribution we report on three recent advances in modularity optimization, namely: 1. The randomized greedy (RG) family of modularity optimization algorithms are state-of-the-art graph clustering algorithms which are near optimal, fast, and scalable. 2. The extension of the RG family to multi-level clustering. 3. A new entropy based cluster index which allows the detection of the proper clustering levels and of stable core clusters at each level. Last, but not least, several marketing applications of these algorithms for customer enablement and empowerment are discussed: e.g. the detection of low-level cluster structures from retail purchase data, the analysis of the co-usage structure of scientific documents for detecting multilevel category structures for scientific libraries, and the analysis of social groups from the friend relation of social network sites

EmergenSIG: an integrated location-based system for emergency management

Several solutions have been proposed for emergencies scenarios. These solutions include real-time data communication, location-aware, coordination, and decision-making support systems. In this context, this dissertation presents a location-awareness system fully oriented to emergency scenarios, called EmergenSIG. This approach provides and gathers important field information from an occurrence (emergency situation) and shares it to all the different agents. They include police, firefighters, medical emergency teams, among others, mobilized to the same operations theater (OT). Therefore, allowing a faster and integrated response to all the involved agents, enhancing the emergency management of the occurrence. The core of this proposal is based on a low cost solution oriented to the agents on the field (EmergenSIG mobile application), which interacts with the EmergenSIG Web application, oriented to the civil protection entities, through REST Web services. EmergenSIG focuses on medical emergencies and wildfires. It was evaluated and demonstrated in different mobile devices considering different screen sizes following a usercentered design. The system was also been evaluated and validated by real entities and civil protection agents on simulated emergency scenarios.Várias soluções têm sido propostas para cenários de emergências médicas . Estas soluções incluem comunicações de dados em tempo real ,sensíveis á localização , coordenação e sistemas de apoio à tomada de decisão. Neste contexto, esta dissertação apresenta um sistema sensível à localização totalmente orientada para cenários de emergência, chamada EmergenSIG. Esta abordagem proporciona e reúne importantes informações de uma ocorrência (situação de emergência) compartilhando-a para todos os diferentes agentes. Nos quais se incluem a polícia, bombeiros, equipas de emergência médica, entre outros, que se mobilizaram para o mesmo teatro de operações (TO). Portanto, permite uma resposta mais rápida e integrada para todos os agentes envolvidos, aumentando a eficácia da gestão da emergência de uma ocorrência. O cerne desta proposta é baseada numa solução de baixo custo direcionada para os agentes no terreno (aplicação móvel EmergenSIG), que interage com o aplicativo Web EmergenSIG, orientada para as entidades da proteção civil, através de serviços Web REST. O EmergenSIG centra-se em emergências médicas e incêndios florestais. Foi avaliada e demonstrada em diferentes dispositivos móveis, considerando diferentes tamanhos de ecrã e seguindo um design centrado no utilizador. O sistema também foi avaliado e validado por entidades reais e agentes da proteção civil em cenários de emergência simulados

Detección de comunidades en redes: Algoritmos y aplicaciones

El presente trabajo de fin de máster tiene como objetivo la realización de un análisis de los métodos de detección de comunidades en redes. Como parte inicial se realizó un estudio de las características principales de la teoría de grafos y las comunidades, así como medidas comunes en este problema. Posteriormente, se realizó una revisión de los principales métodos de detección de comunidades, elaborando una clasificación, teniendo en cuenta sus características y complejidad computacional, para la detección de las fortalezas y debilidades en los métodos, así como también trabajos posteriores. Luego, se estudio el problema de la calificación de un método de agrupamiento, esto con el fin de evaluar la calidad de las comunidades detectadas, analizando diferentes medidas. Por último se elaboraron las conclusiones así como las posibles líneas de trabajo que se pueden derivar.This master's thesis work has the objective of performing an analysis of the methods for detecting communities in networks. As an initial part, I study of the main features of graph theory and communities, as well as common measures in this problem. Subsequently, I was performed a review of the main methods of detecting communities, developing a classification, taking into account its characteristics and computational complexity for the detection of strengths and weaknesses in the methods, as well as later works. Then, study the problem of classification of a clustering method, this in order to evaluate the quality of the communities detected by analyzing different measures. Finally conclusions are elaborated and possible lines of work that can be derived

Special issue: Customer empowerment

The second French-German workshop about Consumer Empowerment took place at the University of Karlsruhe (KIT) between January 10-11, 2013. Within the scope of consumer empowerment scientists discussed recent developments in this field and established cross-disciplinary coop- erations in their own fields of research