infonet-economy

We develop a functional learning approach to modelling systems of time series which preserves the ability of standard linear time-series models (VARs) to uncover the Granger-causality links in between the series of the system while allowing for richer functional relationships. We propose a framework for learning multiple output-kernels associated with multiple input-kernels over a…

This paper investigates theoretically how the structure of means-tested public long-term care (LTC) support influences the relationship between LTC insurance and informal care. Three types of public support encountered in various means-tested LTC schemes are examined. First, the level to be considered for means-testing only takes into account the level of wealth of the recipient…

This paper investigates the effect of changes in ambiguity on the value of statistical life (VSL) under the smooth ambiguity model developed by Klibano, Marinacci and Mukerji (2005). Changes in ambiguity over the mortality risk are expressed through the specific concept of stochastic dominance of order n defined by Ekern (1980). We provide sufficient conditions on the individual…

We investigated two strategies for improving Information Retrieval thanks to incoming and outgoing citations. We first started from settings that worked last year and established a baseline. Then, we tried to rerank this run. The incoming citations’ strategy was to compute the number of incoming citations in PubMed Central, and to boost the score of the articles that were the most…

This study investigates the quay crane allocation problem with respect to vessel assigned to a particular discrete berth at a bulk material handling port. In the proposed model,vessels at the anchorage are berthed on a First in, first out (FIFO) basis at the port, and then the quay cranes are assigned to the berth dynamically before berthing and during unloading of the vessel. To…

The CLEF RepLab 2014 Track was the occasion to investigate the robustness of instance-based learning in a complete system for tweet monitoring and categorization based. The algorithm we implemented was a k-Nearest Neighbors. Dealing with the domain (automotive or banking) and the language (English or Spanish), the experiments showed that the categorizer was not affected by the choice…

We study parametric unsupervised mixture learning. We measure the loss of intrinsic information from the observations to complex mixture models, and then to simple mixture models. We present a geometric picture, where all these representations are regarded as free points in the space of probability distributions. Based on minimum description length, we derive a simple geometric…

In this paper we present reflections and recommendations concerning the conversion of library metadata into Linked Data. We will briefly describe the different data models that exist for this purpose and argue their strengths and weaknesses with a special focus on the entification issue, before illustrating this problem with the description of three different ongoing projects. As…

The literature reveals the complexity of identifying the attributes, the factors and the mechanisms that would influence trust between supply chain partners. Moreover, the way trust influences the performance of a supply chain is still a subject that remains to be thoroughly researched since trust is a subjective issue that has several dimensions. This paper focuses on the influence…