Search results for "machine"
showing 10 items of 2592 documents
Deep neural attention-based model for the evaluation of italian sentences complexity
2020
In this paper, the Automatic Text Complexity Evaluation problem is modeled as a binary classification task tackled by a Neural Network based system. It exploits Recurrent Neural Units and the Attention mechanism to measure the complexity of sentences written in the Italian language. An accurate test phase has been carried out, and the system has been compared with state-of-art tools that tackle the same problem. The computed performances proof the model suitability to evaluate sentence complexity improving the results achieved by other state-of-the-art systems.
A Clustering approach for profiling LoRaWAN IoT devices
2019
Internet of Things (IoT) devices are starting to play a predominant role in our everyday life. Application systems like Amazon Echo and Google Home allow IoT devices to answer human requests, or trigger some alarms and perform suitable actions. In this scenario, any data information, related device and human interaction are stored in databases and can be used for future analysis and improve the system functionality. Also, IoT information related to the network level (wireless or wired) may be stored in databases and can be processed to improve the technology operation and to detect network anomalies. Acquired data can be also used for profiling operation, in order to group devices according…
Risks in neural machine translation
2020
Abstract The new paradigm of neural machine translation is leading to profound changes in the translation industry. Surprisingly good results have led to high expectations; however, there are substantial risks that have not yet been sufficiently taken into account. Risks exist on three levels: first, what kind of damage can clients and end users incur in safety-critical domains if the NMT result contains errors; second, who is liable for damage caused by the use of NMT; third, what cyber risks can the use of NMT entail, especially when free online engines are used. When establishing sustainable measures to reduce such risks, we also need to consider general principles of human behaviour if …
Multi-class Text Complexity Evaluation via Deep Neural Networks
2019
Automatic Text Complexity Evaluation (ATE) is a natural language processing task which aims to assess texts difficulty taking into account many facets related to complexity. A large number of papers tackle the problem of ATE by means of machine learning algorithms in order to classify texts into complex or simple classes. In this paper, we try to go beyond the methodologies presented so far by introducing a preliminary system based on a deep neural network model whose objective is to classify sentences into more of two classes. Experiments have been carried out on a manually annotated corpus which has been preprocessed in order to make it suitable for the scope of the paper. The results sho…
Eventual Consistency Formalized
2019
Distribution of computation is well-known, and there are several frameworks, including some formal frameworks, that capture distributed computation. As yet, however, models of distributed computation are based on the idea that data is conceptually centralized. That is, they assume that data, even if it is distributed, is consistent. This assumption is not valid for many of the database systems in use today, where consistency is compromised to ensure availability and partition tolerance. Starting with an informal definition of eventual consistency, this paper explores several measures of inconsistency that quantify how far from consistency a system is. These measures capture key aspects of e…
Comparing the Quality of Neural Machine Translation and Professional Post-Editing
2019
This empirical corpus study explores the quality of neural machine translations (NMT) and their post-edits (NMTPE) at the German Department of the European Commission’s Directorate-General for Translation (DGT) by evaluating NMT outputs, NMTPE, and respective revisions (REV) with the automatic error annotation tool Hjerson (Popovic 2011) and the more fine-grained manual MQM framework (Lommel 2014). Results show that quality assurance measures by post-editors and revisors at the DGT are most often necessary for lexical errors. More specifically, if post-editors correct mistranslations, terminology or stylistic errors in an NMT sentence, revisors are likely to correct the same type of error i…
SLFTD: A Subjective Logic Based Framework for Truth Discovery
2019
Finding truth from various conflicting candidate values provided by different data sources is called truth discovery, which is of vital importance in data integration. Several algorithms have been proposed in this area, which usually have similar procedure: iteratively inferring the truth and provider’s reliability on providing truth until converge. Therefore, an accurate provider’s reliability evaluation is essential. However, no work pays attention to “how reliable this provider continuously providing truth”. Therefore, we introduce subjective logic, which can record both (1) the provider’s reliability of generating truth, and (2) reliability of provider continuously doing so. Our propose…
Containers in Software Development: A Systematic Mapping Study
2019
Over the past decade, continuous software development has become a common place in the field of software engineering. Containers like Docker are a lightweight solution that developers can use to deploy and manage applications. Containers are used to build both component-based architectures and microservice architectures. Still, practitioners often view containers only as way to lower resource requirements compared to virtual machines. In this paper, we conducted a systematic mapping study to find information on what is known of how containers are used in software development. 56 primary studies were selected into this paper and they were categorized and mapped to identify the gaps in the cu…
Models of the Translation Process
2017
Training the modern translator – the acquisition of digital competencies through blended learning
2019
This paper presents the ERASMUS+ DigiLing project, which aims to teach and improve linguists’ and translators’ skills and knowledge of digitalisation to prepare them for today’s job market. Against this background, it discusses the development of digital competencies and distinguishes them from traditional domain-specific and general competencies. For the purpose of competence acquisition, six online courses have been created which all revolve around the field of ‘digital linguistics’, including localization in the digital age and post-editing machine translation. We provide an overview of the project, the course contents and the didactic methodology. In addition, we discuss which competenc…