An architecture for certification-aware service discovery

Service-orientation is an emerging paradigm for building complex systems based on loosely coupled components, deployed and consumed over the network. Despite the original intent of the paradigm, its current instantiations are limited to a single trust domain (e.g., a single organization). Also, some of the key promises of service-orientation - such as the dynamic orchestration of externally provided software services, using runtime service discovery and deployment - are still unachieved. One of the main reasons for this is the trust gap that normally arises when software services, offered by previously unknown providers, are to be selected at run-time, without any human intervention. To close this gap, the concept of machine-readable security certificates (called asserts) has been recently introduced, which paves the way to automated processing about security properties of services. Similarly to current security certification schemes, the assessment of the security properties of a service is delegated to an independent third party (certification authority), who issues a corresponding assert, bound to the service. In this paper, we propose an architecture, which exploits the assert concept to realise a certification-aware service discovery framework. The architecture supports the discovery of single services based on certified security properties (in additional to the usual functional properties), as well as the dynamic synthesis of service compositions, that satisfy the given security properties. The architecture is extensible, thus allowing for a range of domain specific matchmaking components, to cover dimensions related to, e.g., performance, cost and other non-functional characteristics

Query DAGs: A Practical Paradigm for Implementing Belief-Network Inference

We describe a new paradigm for implementing inference in belief networks, which consists of two steps: (1) compiling a belief network into an arithmetic expression called a Query DAG (Q-DAG); and (2) answering queries using a simple evaluation algorithm. Each node of a Q-DAG represents a numeric operation, a number, or a symbol for evidence. Each leaf node of a Q-DAG represents the answer to a network query, that is, the probability of some event of interest. It appears that Q-DAGs can be generated using any of the standard algorithms for exact inference in belief networks (we show how they can be generated using clustering and conditioning algorithms). The time and space complexity of a Q-DAG generation algorithm is no worse than the time complexity of the inference algorithm on which it is based. The complexity of a Q-DAG evaluation algorithm is linear in the size of the Q-DAG, and such inference amounts to a standard evaluation of the arithmetic expression it represents. The intended value of Q-DAGs is in reducing the software and hardware resources required to utilize belief networks in on-line, real-world applications. The proposed framework also facilitates the development of on-line inference on different software and hardware platforms due to the simplicity of the Q-DAG evaluation algorithm. Interestingly enough, Q-DAGs were found to serve other purposes: simple techniques for reducing Q-DAGs tend to subsume relatively complex optimization techniques for belief-network inference, such as network-pruning and computation-caching.Comment: See http://www.jair.org/ for any accompanying file

Adapting Binary Information Retrieval Evaluation Metrics for Segment-based Retrieval Tasks

This report describes metrics for the evaluation of the effectiveness of segment-based retrieval based on existing binary information retrieval metrics. This metrics are described in the context of a task for the hyperlinking of video segments. This evaluation approach re-uses existing evaluation measures from the standard Cranfield evaluation paradigm. Our adaptation approach can in principle be used with any kind of effectiveness measure that uses binary relevance, and for other segment-baed retrieval tasks. In our video hyperlinking setting, we use precision at a cut-off rank n and mean average precision.Comment: Explanation of evaluation measures for the linking task of the MediaEval Workshop 201

Assessing Visualization Techniques for the Search Process in Digital Libraries

In this paper we present an overview of several visualization techniques to support the search process in Digital Libraries (DLs). The search process typically can be separated into three major phases: query formulation and refinement, browsing through result lists and viewing and interacting with documents and their properties. We discuss a selection of popular visualization techniques that have been developed for the different phases to support the user during the search process. Along prototypes based on the different techniques we show how the approaches have been implemented. Although various visualizations have been developed in prototypical systems very few of these approaches have been adapted into today's DLs. We conclude that this is most likely due to the fact that most systems are not evaluated intensely in real-life scenarios with real information seekers and that results of the interesting visualization techniques are often not comparable. We can say that many of the assessed systems did not properly address the information need of cur-rent users.Comment: 23 pages, 14 figures, pre-print to appear in "Wissensorganisation mit digitalen Technologien" (deGruyter