We consider the problem of dividing some amount of an infinitely divisible and homogeneous resource among agents having claims on this resource that cannot be jointly honored. A “rule” associates with each such problem a feasible division. Our goal is to uncover the structure of the space of rules. For that purpose, we study “operators” on the space, that is, mappings that associate to each rul...

We consider the problem of allocating some amount of an infinitely divisible and homogeneous resource among agents having claims on this resource that cannot be jointly honored. A “rule” associates with each such problem a feasible division. Our goal is to uncover the structure of the space of rules. For that purpose, we study “operators” on the space, that is, mappings that associate to each r...

Organizational boards of directors are one of the most important subgroups within most modern organizations, performing critical advisory, monitoring and resource dependence roles. This paper investigates the crucial question of whether the stock market values ethnic and gender diversity within organizational boards. We find that board diversity is positively associated with market valuation. W...

This work addresses the classification of word pairs as instances of lexical-semantic relations. The classification is approached by leveraging patterns of co-occurrence contexts from corpus data. The significance of using dependency information, of augmenting the set of dependency paths provided to the system, and of generalizing patterns using part-of-speech information for the classification...

The paper addresses the challenge of converting MIDT, an existing dependency– based Italian treebank resulting from the harmonization and merging of smaller resources, into the Stanford Dependencies annotation formalism, with the final aim of constructing a standard–compliant resource for the Italian language. Achieved results include a methodology for converting treebank annotations belonging ...

We present a novel approach for inducing unsupervised dependency parsers for languages that have no labeled training data, but have translated text in a resourcerich language. We train probabilistic parsing models for resource-poor languages by transferring cross-lingual knowledge from resource-rich language with entropy regularization. Our method can be used as a purely monolingual dependency ...

We announce a new language resource for research on semantic parsing, a large, carefully curated collection of semantic dependency graphs representing multiple linguistic traditions. This resource is called SDP 2016 and provides an update and extension to previous versions used as Semantic Dependency Parsing target representations in the 2014 and 2015 Semantic Evaluation Exercises (SemEval). Fo...

In this paper, we propose a resource management system in Grid computing in order to specify system Quality of Service (QoS) requirements for dynamic and complex emerging applications. Our approach is based on the functional dependency among application components to specify the probability of system QoS requirements for the emerging application. Experimental results show that our application s...

Spillovers have attracted wide attention in the areas of research in economics during the past decades. The reason for the interest in the topic lies in their important role in endogenous growth theory and the explanation of productivity growth. This paper investigates the spatial spillover of different types of public infrastructure on economic growth across EU-28 NUTS-II regions during 1995-2...

 The importance of community's health followed by the consideration of endogenous growth models has led to an increase in health expenditure of countries to speed up economic growth and development. This has made the efficiency of health production function to an essential issue especially in developing countries. Based upon this, the present study with employing the stochastic frontier analysi...