A review of the role of sensors in mobile context-aware recommendation systems

Recommendation systems are specialized in offering suggestions about specific items of different types (e.g., books, movies, restaurants, and hotels) that could be interesting for the user. They have attracted considerable research attention due to their benefits and also their commercial interest. Particularly, in recent years, the concept of context-aware recommendation system has appeared to emphasize the importance of considering the context of the situations in which the user is involved in order to provide more accurate recommendations. The detection of the context requires the use of sensors of different types, which measure different context variables. Despite the relevant role played by sensors in the development of context-aware recommendation systems, sensors and recommendation approaches are two fields usually studied independently. In this paper, we provide a survey on the use of sensors for recommendation systems. Our contribution can be seen from a double perspective. On the one hand, we overview existing techniques used to detect context factors that could be relevant for recommendation. On the other hand, we illustrate the interest of sensors by considering different recommendation use cases and scenarios

A semantic framework for event-driven service composition

Title from PDF of title page, viewed on September 14, 2011VitaDissertation advisor: Yugyung LeeIncludes bibliographical references (p. 289-329)Thesis (Ph.D)--School of Computing and Engineering. University of Missouri--Kansas City, 2011Service Oriented Architecture (SOA) has become a popular paradigm for designing distributed systems where loosely coupled services (i.e. computational entities) can be integrated seamlessly to provide complex composite services. Key challenges are discovery of the required services using their formal descriptions and their coherent composition in a timely manner. Most service descriptions are written in XML-based languages that are syntactic, creating linguistic ambiguity during service matchmaking. Furthermore, existing models that implement SOA have mostly middleware-controlled synchronous request/replybased runtime binding of services that incur undesirable service latency. In addition, they impose expensive state monitoring overhead on the middleware. Some newer event-driven models introduce asynchronous publish/subscribe-based event notifications to consumer applications and services. However, they require an event-library that stores definitions of all possible system events, which is impractical in an open and dynamic system. The objective of this study is to efficiently address on-demand consumer requests with minimum service latency and maximum consumer utility. It focuses on semantic eventdriven service composition. For efficient semantic service discovery, the dissertation proposes a novel service learning algorithm called Semantic Taxonomic Clustering (STC). The algorithm utilizes semantic service descriptions to cluster services into functional categories for pruning search space during service discovery and composition. STC utilizes a dynamic bit-encoding algorithm called DL-Encoding that enables linear time bit operationbased semantic matchmaking as compared to expensive reasoner-based semantic matchmaking. The algorithm shows significant improvement in performance and accuracy over some of the important service category algorithms reported in the literature. A novel user-friendly and computationally efficient query model called Desire-based Query Model (DQM) is proposed for formally specifying service queries. STC and DQM serve as the building block for the dual framework that is the core contribution of this dissertation: (i) centralized ALNet (Activity Logic Network) platform and (ii) distributed agentbased SMARTSPACE platform. The former incorporates a middleware controlled service composition algorithm called ALNetComposer while the latter includes the SmartDeal purely distributed composition algorithm. The query response accuracy and performance were evaluated for both the algorithms under simulated event-driven SOA environments. The experimental results show that various environmental parameters, such as domain diversity and scope, size and complexity of the SOA system, and dynamicity of the SOA system, significantly affect accuracy and performance of the proposed model. This dissertation demonstrates that the functionality and scalability of the proposed framework are acceptable for relatively static and domain specific environments as well as large, diverse, and highly dynamic environments. In summary, this dissertation addresses the key design issues and problems in the area of asynchronous and pro-active event-driven service composition.Introduction -- Research background -- Semantic service matchmaking & query modeling -- Service organization by learning service category -- ALNet: event-driven platform for service composition -- SMARTSPACE: distributed multi-agent based event-handeling -- Conclusion & future wor

C-EMO: A Modeling Framework for Collaborative Network Emotions

Recent research in the area of collaborative networks is focusing on the social and organizational complexity of collaboration environments as a way to prevent technological failures and consequently contribute for the collaborative network’s sustainability. One direction is moving towards the need to provide “human-tech” friendly systems with cognitive models of human factors such as stress, emotion, trust, leadership, expertise or decision-making ability. In this context, an emotion-based system is being proposed with this thesis in order to bring another approach to avoid collaboration network’s failures and help in the management of conflicts. This approach, which is expected to improve the performance of existing CNs, adopts some of the models developed in the human psychology, sociology and affective computing areas. The underlying idea is to “borrow” the concept of human-emotion and apply it into the context of CNs, giving the CN players the ability to “feel emotions”. Therefore, this thesis contributes with a modeling framework that conceptualizes the notion of “emotion” in CNs and a methodology approach based on system dynamics and agent-based techniques that estimates the CN player’s “emotional states” giving support to decision-making processes. Aiming at demonstrating the appropriateness of the proposed framework a simulation prototype was implemented and a validation approach was proposed consisting of simulation of scenarios, qualitative assessment and validation by research community peers.Recentemente a área de investigação das redes colaborativas tem vindo a debruçar-se na complexidade social e organizacional em ambientes colaborativos e como pode ser usada para prevenir falhas tecnológicas e consequentemente contribuir para redes colaborativas sustentáveis. Uma das direcções de estudo assenta na necessidade de fornecer sistemas amigáveis “humano-tecnológicos” com modelos cognitivos de factores humanos como o stress, emoção, confiança, liderança ou capacidade de tomada de decisão. É neste contexto que esta tese propõe um sistema baseado em emoções com o objectivo de oferecer outra aproximação para a gestão de conflitos e falhas da rede de colaboração. Esta abordagem, que pressupõe melhorar o desempenho das redes existentes, adopta alguns dos modelos desenvolvidos nas áreas da psicologia humana, sociologia e affective computing. A ideia que está subjacente é a de “pedir emprestado” o conceito de emoção humana e aplicá-lo no contexto das redes colaborativas, dando aos seus intervenientes a capacidade de “sentir emoções”. Assim, esta tese contribui com uma framework de modelação que conceptualiza a noção de “emoção” em redes colaborativas e com uma aproximação de metodologia sustentada em sistemas dinâmicos e baseada em agentes que estimam os “estados emocionais” dos participantes e da própria rede colaborativa. De forma a demonstrar o nível de adequabilidade da framework de modelação proposta, foi implementado um protótipo de simulação e foi proposta uma abordagem de validação consistindo em simulação de cenários, avaliação qualitativa e validação pelos pares da comunidade científica