Exploring automatic feature selection for transition-based dependency parsing

En este artículo se investigan técnicas automáticas para encontrar un modelo óptimo de características en el caso de un analizador de dependencias basado en transiciones. Mostramos un estudio comparativo entre algoritmos de búsqueda, sistemas de validación y reglas de decisión demostrando al mismo tiempo que usando nuestros métodos es posible conseguir modelos complejos que proporcionan mejores resultados que los modelos que siguen configuraciones por defecto.

Benefits of the ISO 9001 and ISO 14001 standards: a literature review

Purpose: The purpose of this paper is to determine the similarities and differences between the benefits derived from implementing the ISO 9001 and the ISO 14001 standards. Methodology/Approach: The paper reviews the literature using an electronic search in the ScienceDirect, ABI/Inform, Emerald databases to identify papers focusing on the adoption of the ISO 9001 and 14001 standards and the benefits derived from implementing them. Findings: The paper identifies 82 articles about ISO 9001 and 29 about ISO 14001. Although some differences can be observed between the benefits considered by ISO 9001 and 14001, there is a great degree of coincidence in the benefits studied. The review suggests 13 benefits as the most usually analyzed (including environmental performance for the case of the ISO 14001 standard) by scholars. It is suggested that both standards have clear benefits on operational, people and customer results and that the effects on financial performance are inconclusive. Limitations/implications: One limitation of this paper is that the works identified are conditioned by the search strategy used. In addition, other key words could be included in future studies such as operational, market, quality, financial performance, and customer satisfaction in order to expand this search. Originality/Value: The main contribution is that the paper identifies the literature gap and future research proposals with regard to the benefits of the ISO 9001 and ISO 14001 standards.

Algorithm for the detection of outliers based on the theory of rough sets

Outliers are objects that show abnormal behavior with respect to their context or that have unexpected values in some of their parameters. In decision-making processes, information quality is of the utmost importance. In specific applications, an outlying data element may represent an important deviation in a production process or a damaged sensor. Therefore, the ability to detect these elements could make the difference between making a correct and an incorrect decision. This task is complicated by the large sizes of typical databases. Due to their importance in search processes in large volumes of data, researchers pay special attention to the development of efficient outlier detection techniques. This article presents a computationally efficient algorithm for the detection of outliers in large volumes of information. This proposal is based on an extension of the mathematical framework upon which the basic theory of detection of outliers, founded on Rough Set Theory, has been constructed. From this starting point, current problems are analyzed; a detection method is proposed, along with a computational algorithm that allows the performance of outlier detection tasks with an almost-linear complexity. To illustrate its viability, the results of the application of the outlier-detection algorithm to the concrete example of a large database are presented.