Model-driven design, simulation and implementation of service compositions in COSMO

The success of software development projects to a large extent depends on the quality of the models that are produced in the development process, which in turn depends on the conceptual and practical support that is available for modelling, design and analysis. This paper focuses on model-driven support for service-oriented software development. In particular, it addresses how services and compositions of services can be designed, simulated and implemented. The support presented is part of a larger framework, called COSMO (COnceptual Service MOdelling). Whereas in previous work we reported on the conceptual support provided by COSMO, in this paper we proceed with a discussion of the practical support that has been developed. We show how reference models (model types) and guidelines (design steps) can be iteratively applied to design service compositions at a platform independent level and discuss what tool support is available for the design and analysis during this phase. Next, we present some techniques to transform a platform independent service composition model to an implementation in terms of BPEL and WSDL. We use the mediation scenario of the SWS challenge (concerning the establishment of a purchase order between two companies) to illustrate our application of the COSMO framework

Managing contextual information in semantically-driven temporal information systems

Context-aware (CA) systems have demonstrated the provision of a robust solution for personalized information delivery in the current content-rich and dynamic information age we live in. They allow software agents to autonomously interact with users by modeling the user’s environment (e.g. profile, location, relevant public information etc.) as dynamically-evolving and interoperable contexts. There is a flurry of research activities in a wide spectrum at context-aware research areas such as managing the user’s profile, context acquisition from external environments, context storage, context representation and interpretation, context service delivery and matching of context attributes to users‘ queries etc. We propose SDCAS, a Semantic-Driven Context Aware System that facilitates public services recommendation to users at temporal location. This paper focuses on information management and service recommendation using semantic technologies, taking into account the challenges of relationship complexity in temporal and contextual information

The Influence of Corporate Social Responsibility Activity Toward Customer Loyalty Through Improvement of Quality of Life in Urban Area

The success of Corporate Social Responsibility (CSR) activities can create competitive advantage by influencing customer responses to firms’ offering. Customer’s awareness of CSR activity will influence their loyalty through their perception that activity can improve society’s quality of life where the CSR activities were implemented. The objective of this study is to evaluate the relationship between CSR awareness and loyalty that mediated by CSR Belief, Company Ability Belief, Quality of Life, and Company Reputation using Structural Equation Modelling (SEM). The result shows little differrences among five firms/brands as the object of the research, that are beverage, soap, car, lubricant, and cigarette. This result has an implication for the firm that CSR activities are not just cost center activities, but also can create reputation, and in the long run can create customer loyalty that contributes to firm’s financial benefit

Approaches to Semantic Web Services: An Overview and Comparison

Abstract. The next Web generation promises to deliver Semantic Web Services (SWS); services that are self-described and amenable to automated discovery, composition and invocation. A prerequisite to this, however, is the emergence and evolution of the Semantic Web, which provides the infrastructure for the semantic interoperability of Web Services. Web Services will be augmented with rich formal descriptions of their capabilities, such that they can be utilized by applications or other services without human assistance or highly constrained agreements on interfaces or protocols. Thus, Semantic Web Services have the potential to change the way knowledge and business services are consumed and provided on the Web. In this paper, we survey the state of the art of current enabling technologies for Semantic Web Services. In addition, we characterize the infrastructure of Semantic Web Services along three orthogonal dimensions: activities, architecture and service ontology. Further, we examine and contrast three current approaches to SWS according to the proposed dimensions

For the Public's Health: The Role of Measurement in Action and Accountability

Outlines a framework for the collection, analysis, and dissemination of population health data that help assess the social, economic, and environmental factors affecting health to increase clinical effectiveness and enhance government accountability

Unbiased Offline Evaluation of Contextual-bandit-based News Article Recommendation Algorithms

Contextual bandit algorithms have become popular for online recommendation systems such as Digg, Yahoo! Buzz, and news recommendation in general. \emph{Offline} evaluation of the effectiveness of new algorithms in these applications is critical for protecting online user experiences but very challenging due to their "partial-label" nature. Common practice is to create a simulator which simulates the online environment for the problem at hand and then run an algorithm against this simulator. However, creating simulator itself is often difficult and modeling bias is usually unavoidably introduced. In this paper, we introduce a \emph{replay} methodology for contextual bandit algorithm evaluation. Different from simulator-based approaches, our method is completely data-driven and very easy to adapt to different applications. More importantly, our method can provide provably unbiased evaluations. Our empirical results on a large-scale news article recommendation dataset collected from Yahoo! Front Page conform well with our theoretical results. Furthermore, comparisons between our offline replay and online bucket evaluation of several contextual bandit algorithms show accuracy and effectiveness of our offline evaluation method.Comment: 10 pages, 7 figures, revised from the published version at the WSDM 2011 conferenc