Contributions in Merlin

Finding good algorithms for assessing the similarity of complex objects in ontologies is central to the functioning of techniques such as retrieval, matchmaking, clustering, data-mining, semantic sense disambiguation, ontology translations, and simple object comparisons. These techniques provide the basis for supporting a wide variety of business intelligence computing tasks like finding a process in a best practice repository, finding a suitable service provider/outsourcing partner for agile process enactment, dynamic customer segmentation, semantic web applications, and systems integration. To our knowledge, however, there exists no study that systematically compares the prediction quality of ontology based similarity measures. This paper assembles a catalogue of ontology based similarity measures that are (partially) adapted from related domains. These measures are compared to each other within a large, real-world best practice ontology as well as evaluated in a realistic business process retrieval scenario. We find that different similarity algorithms reflect different notions of similarity. We also show how a combination of similarity measures can be used to improve both precision and recall of an ontology-based, query-by-example style, object retrieval approach. Combining the study’s findings with the literature we argue for the need of extended studies to assemble a more complete catalogue of object similarity measures that can be evaluated in many applications and ontologies.

During the 1990s, the social health insurance schemes of Germany, the Netherlands, Switzerland, Belgium and Israel were significantly reformed by the introduction of freedom of choice (open enrolment) of health insurer. This was introduced alongside a system of risk adjustment to compensate health insurers for enrolees with predictable high medical expenses. Despite the similarity in the health insurance reforms in these countries, we find that both the rationale behind these reforms and their impact on consumer choice vary widely. In this article we seek to explain the observed variation in switching rates by cross-country comparison of the potential determinants of health insurer choice. We conclude that differences in choice setting, and in the net benefits of switching, offer a plausible explanation for the large differences in consumer mobility. Finally, we discuss the policy implications of our cross-country comparison. We argue that the optimal switching rate crucially depends on the goals of the reforms and the quality of the risk-adjustment system. In view of this, we conclude that switching rates are currently too low in the Netherlands, and an active government policy to encourage consumer mobility seems warranted. In Germany and Switzerland, high switching rates call for an improvement of the rather poor risk-adjustment systems. Given low switching rates in Israel and Belgium, improving risk adjustment is less urgent, but still required in the long run.

In this paper, we present TUAnalyzer, a novel tool that extracts the template structure of C++ programs on the basis of the GNU C/C++ Compiler’s internal representation of a C/C++ translation unit. In comparison to other such tools, our tool is capable of supporting the extraction of function invocations that depend on the particular instantiation of C++ templates and to relate them to their particular template instantiation. TUAnalyzer produces RSF format output that can be easily fed into existing visualization and analysis tools such as Rigi or Graphviz. We motivate why this kind of template analysis information is essential to understand real-world legacy C++ applications. We present how our tool extracts this kind of information to allow others to build on our results and further use the template information. The applicability of our tool has been validated on real code as proof of concept. The results obtained with TUAnalyzer enable us and other approaches and tools to perform detailed studies of large (open source) C/C++ projects in the near future.

The idea to learn about international capital mobility from saving and investment data remains appealing. Our approach is based on VAR methods and overcomes some of the problems associated with saving–investment regressions when the data are non-stationary. We propose a new measure of long-run capital mobility that can be easily calculated as a by-product of the estimation procedure of a cointegrated VAR. In an application to historical US and British data, we find long-run capital mobility to have been remarkably stable over the century whereas variations in the mobility of capital primarily seem to have affected short-run capital flows.

null

null

In this article the problem of the American option valuation in a Lévy process setting is analysed. The perpetual case is first considered. Without possible discontinuities (i.e. with negative jumps in the call case), known results concerning the currency option value as well as the exercise boundary are obtained with a martingale approach. With possible discontinuities of the underlying process at the exercise boundary (i.e. with positive jumps in the call case), original results are derived by relying on first passage time and overshoot associated with a Lévy process. For finite life American currency calls, the formula derived by Bates or Zhang, in the context of a negative jump size, is tested. It is basically an extension of the one developed by Mac Millan and extended by Barone‐Adesi and Whaley. It is shown that Bates' model generates pretty good results only when the process is continuous at the exercise boundary.

null

Discovering the interactions between genes and proteins is seen as one of the core tasks in molecular biology. The quantity of research results in this area is growing at such a rate that it is very di?cult for individual researchers to keep track of them. As such results appear mainly in the form of scienti?c articles, it is necessary to process them in an e?cient manner in order to be able to extract the relevant results. Many databases exist that aim at consolidating the newly gained knowledge in a format that is easily accessible and searchable, however the creators of such databases normally make use of human readers who manually ‘curate’ the rel- evant papers. This is an expensive and time consuming process, besides, there might be a signi?cant time lag be- tween the publication of a result and its introduction into such databases. In this paper we propose a method for discovery of inter- actions between genes and proteins from the scienti?c liter- ature, based on a complete syntactic analysis of the corpus. We report on preliminary results.