Extracting fine-grained economic events from business news

Based on a recently developed fine-grained event extraction dataset for the economic domain, we present in a pilot study for supervised economic event extraction. We investigate how a state-of-the-art model for event extraction performs on the trigger and argument identification and classification. While F1-scores of above 50{%} are obtained on the task of trigger identification, we observe a large gap in performance compared to results on the benchmark ACE05 dataset. We show that single-token triggers do not provide sufficient discriminative information for a fine-grained event detection setup in a closed domain such as economics, since many classes have a large degree of lexico-semantic and contextual overlap

Completeness, robustness, and safety in real-time software requirements specification

This paper presents an approach to providing a rigorous basis for ascertaining whether or not a given set of software requirements is internally complete, i.e., closed with respect to questions and inferences that can be made on the basis of information included in the specification. Emphasis is placed on aspects of software requirements specifications that previously have not been adequately handled, including timing abstractions, safety, and robustness

Knowledge Expansion of a Statistical Machine Translation System using Morphological Resources

Translation capability of a Phrase-Based Statistical Machine Translation (PBSMT) system mostly depends on parallel data and phrases that are not present in the training data are not correctly translated. This paper describes a method that efficiently expands the existing knowledge of a PBSMT system without adding more parallel data but using external morphological resources. A set of new phrase associations is added to translation and reordering models; each of them corresponds to a morphological variation of the source/target/both phrases of an existing association. New associations are generated using a string similarity score based on morphosyntactic information. We tested our approach on En-Fr and Fr-En translations and results showed improvements of the performance in terms of automatic scores (BLEU and Meteor) and reduction of out-of-vocabulary (OOV) words. We believe that our knowledge expansion framework is generic and could be used to add different types of information to the model.JRC.G.2-Global security and crisis managemen

Management consulting.

Including a lengthy, comprehensive introduction, this important collection brings together some of the most influential papers that have contributed to our understanding of management consultancy work. The two-volume set encompasses the breadth of conceptual and empirical perspectives and explores those key ideas that have helped to advance our knowledge of this intriguing area. The volumes are divided into a series of thematic sections, affording the reader easy access to a great resource of information. Professors Clark and Avakian have written an original introduction which provides a comprehensive overview of the literature