Using Cross-Lingual Explicit Semantic Analysis for Improving Ontology Translation

Semantic Web aims to allow machines to make inferences using the explicit conceptualisations contained in ontologies. By pointing to ontologies, Semantic Web-based applications are able to inter-operate and share common information easily. Nevertheless, multilingual semantic applications are still rare, owing to the fact that most online ontologies are monolingual in English. In order to solve this issue, techniques for ontology localisation and translation are needed. However, traditional machine translation is difficult to apply to ontologies, owing to the fact that ontology labels tend to be quite short in length and linguistically different from the free text paradigm. In this paper, we propose an approach to enhance machine translation of ontologies based on exploiting the well-structured concept descriptions contained in the ontology. In particular, our approach leverages the semantics contained in the ontology by using Cross Lingual Explicit Semantic Analysis (CLESA) for context-based disambiguation in phrase-based Statistical Machine Translation (SMT). The presented work is novel in the sense that application of CLESA in SMT has not been performed earlier to the best of our knowledge.

CSR Policies: Effects on Labour Productivity in Spanish Micro and Small Manufacturing Companies

This paper analyses empirical evidence of efforts to enable Spanish micro and small manufacturing companies to boost their labour productivity rates through the development of the main pillars of their corporate social responsibility (CSR) policies. This study aims to develop new approaches and sensibilities towards work from an ethical, values (virtues) and CSR perspective, showing how internal dimensions of CSR, such those related to relationships with employees and responsibility in processes and product quality, can improve labour performance and labour efficiency, thereby contributing to a better society. The results of a sample of 929 small businesses indicate that the social responsibility policies that most contributed to a short-term increase in labour productivity are those related to internal aspects of the company, in particular its involvement in the quality of processes and products, promotion of innovation and employee care. However, the impact on labour productivity of CSR policies related to external factors, such as relationship with stakeholders and environmental concern, could not be empirically proven in this paper.

Factors impacting the market share of Construction and Demolition (C&D) Waste recycling solutions

Current EU Directives force the Member States to assure by 2020 that 70% of the Construction and Demolition (C&D) waste is recovered instead of landfilled. While some countries have largely achieved this target, others still have a long way to go. For better understanding the differences arising from local disparities, six factors related to technical, economic, legislative and environmental aspects have been identified as crucial influences in the market share of C&D waste recycling solutions. These factors are able to identify the causes that limit the recycling rate of a certain region. Moreover, progress towards an efficient waste management can vary through the improvement of a single factor. This study provides the background for further fine-tuning the factors and their combination into a mathematical model for assessing the market share of C&D recycling solutions.