In this presentation, we focus on integrating machine translation (MT) into an existing corporate localization and translation workflow. This MT extended workflow includes a customized postediting sub-workflow together with crowdsourced, incentives based translation evaluation feedback routines that enable automated learning processes. The core of the implementation is a semantic repository tha...

Lowfield Park in Sheffield, UK is a green recreational space maintained by the City Council. Lowfield Park was selected as the primary Sheffield FieldLab for the ProFit project which ended in 2015. The ProFit project was European Interreg IVbNWE funded with the aim of encouraging physical activity through innovations in products, services and ICT systems. In 2014 the Sheffield Hallam University...

In this paper, we propose a construction and enrichment process of ontologies from texts. Ontologies are formal structures in which the concepts of a domain and relationships between them are formally defined. An increasing number of papers are dealing with ontologies but their construction and enrichment processes still a problem. Our construction approach is based on terms’s research into tex...

In a language with procedures and pointers as parameters, an instruction can modify memory locations anywhere in the call-stack. The presence of such side effects breaks most generic interprocedural analysis methods, which assume that only the top of the stack may be modified. We present a method that addresses this issue, based on the definition of an equivalent local semantics in which writin...

Machine learning and knowledge acquisition from experts have distinct and apparently complementary knowledge acquisition capabilities. This study demonstrates that the integration of these approaches can both improve the accuracy of the knowledge base that is developed and reduce the time taken to develop it. The system studied, called The Knowledge Factory is distinguished by the manner in whi...

Regular correspondences between historically related languages can be modelled using finitestate transducers (FST). A new method is presented by demonstrating it with a bidirectional experiment between Finnish and Estonian. An artificial representation (resembling a protolanguage) is established between two related languages. This representation, AFE (Aligned Finnish-Estonian) is based on the l...

Gene co-expression network differential analysis is designed to help biologists understand gene expression patterns under different conditions. We have implemented an R package called MODA (Module Differential Analysis) for gene co-expression network differential analysis. Based on transcriptomic data, MODA can be used to estimate and construct condition-specific gene co-expression networks, an...

A constraint is a relation with an active behavior. For a given relation, we propose to learn a representation adapted to this active behavior. It yields two contributions. The first is a generic metatechnique for classifier improvement showing performances comparable to boosting. The second lies in the ability of using the learned concept in constraint-based decision or optimization problems. ...

Computer-aided translation (CAT) system is the most popular tool which helps human translators perform language translation efficiently. To further improve the efficiency, there is an increasing interest in applying the machine translation (MT) technology to upgrade CAT. Post-editing is a standard approach: human translators generate the translation by correcting MT outputs. In this paper, we p...

We design and evaluate several models for integrating Machine Translation (MT) output into a Translation Memory (TM) environment to facilitate the adoption of MT technology in the localization industry. We begin with the integration on the segment level via translation recommendation and translation reranking. Given an input to be translated, our translation recommendation model compares the ou...