45,789 research outputs found

    Improving the translation environment for professional translators

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    When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as well as from a purely technological side. This paper describes the SCATE research with respect to improved fuzzy matching, parallel treebanks, the integration of translation memories with machine translation, quality estimation, terminology extraction from comparable texts, the use of speech recognition in the translation process, and human computer interaction and interface design for the professional translation environment. For each of these topics, we describe the experiments we performed and the conclusions drawn, providing an overview of the highlights of the entire SCATE project

    Design Fiction Diegetic Prototyping: A Research Framework for Visualizing Service Innovations

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    The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose: This paper presents a design fiction diegetic prototyping methodology and research framework for investigating service innovations that reflect future uses of new and emerging technologies. Design/methodology/approach: Drawing on speculative fiction, we propose a methodology that positions service innovations within a six-stage research development framework. We begin by reviewing and critiquing designerly approaches that have traditionally been associated with service innovations and futures literature. In presenting our framework, we provide an example of its application to the Internet of Things (IoT), illustrating the central tenets proposed and key issues identified. Findings: The research framework advances a methodology for visualizing future experiential service innovations, considering how realism may be integrated into a designerly approach. Research limitations/implications: Design fiction diegetic prototyping enables researchers to express a range of ‘what if’ or ‘what can it be’ research questions within service innovation contexts. However, the process encompasses degrees of subjectivity and relies on knowledge, judgment and projection. Practical implications: The paper presents an approach to devising future service scenarios incorporating new and emergent technologies in service contexts. The proposed framework may be used as part of a range of research designs, including qualitative, quantitative and mixed method investigations. Originality: Operationalizing an approach that generates and visualizes service futures from an experiential perspective contributes to the advancement of techniques that enables the exploration of new possibilities for service innovation research

    Visual analytics for supply network management: system design and evaluation

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    We propose a visual analytic system to augment and enhance decision-making processes of supply chain managers. Several design requirements drive the development of our integrated architecture and lead to three primary capabilities of our system prototype. First, a visual analytic system must integrate various relevant views and perspectives that highlight different structural aspects of a supply network. Second, the system must deliver required information on-demand and update the visual representation via user-initiated interactions. Third, the system must provide both descriptive and predictive analytic functions for managers to gain contingency intelligence. Based on these capabilities we implement an interactive web-based visual analytic system. Our system enables managers to interactively apply visual encodings based on different node and edge attributes to facilitate mental map matching between abstract attributes and visual elements. Grounded in cognitive fit theory, we demonstrate that an interactive visual system that dynamically adjusts visual representations to the decision environment can significantly enhance decision-making processes in a supply network setting. We conduct multi-stage evaluation sessions with prototypical users that collectively confirm the value of our system. Our results indicate a positive reaction to our system. We conclude with implications and future research opportunities.The authors would like to thank the participants of the 2015 Businessvis Workshop at IEEE VIS, Prof. Benoit Montreuil, and Dr. Driss Hakimi for their valuable feedback on an earlier version of the software; Prof. Manpreet Hora for assisting with and Georgia Tech graduate students for participating in the evaluation sessions; and the two anonymous reviewers for their detailed comments and suggestions. The study was in part supported by the Tennenbaum Institute at Georgia Tech Award # K9305. (K9305 - Tennenbaum Institute at Georgia Tech Award)Accepted manuscrip

    From Word to Sense Embeddings: A Survey on Vector Representations of Meaning

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    Over the past years, distributed semantic representations have proved to be effective and flexible keepers of prior knowledge to be integrated into downstream applications. This survey focuses on the representation of meaning. We start from the theoretical background behind word vector space models and highlight one of their major limitations: the meaning conflation deficiency, which arises from representing a word with all its possible meanings as a single vector. Then, we explain how this deficiency can be addressed through a transition from the word level to the more fine-grained level of word senses (in its broader acceptation) as a method for modelling unambiguous lexical meaning. We present a comprehensive overview of the wide range of techniques in the two main branches of sense representation, i.e., unsupervised and knowledge-based. Finally, this survey covers the main evaluation procedures and applications for this type of representation, and provides an analysis of four of its important aspects: interpretability, sense granularity, adaptability to different domains and compositionality.Comment: 46 pages, 8 figures. Published in Journal of Artificial Intelligence Researc
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