1,559 research outputs found

    Bridging the gap within text-data analytics: A computer environment for data analysis in linguistic research

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    [EN] Since computer technology became widespread available at universities during the last quarter of the twentieth century, language researchers have been successfully employing software to analyse usage patterns in corpora. However, although there has been a proliferation of software for different disciplines within text-data analytics, e.g. corpus linguistics, statistics, natural language processing and text mining, this article demonstrates that any computer environment intended to support advanced linguistic research more effectively should be grounded on a user-centred approach to holistically integrate cross-disciplinary methods and techniques in a linguist-friendly manner. To this end, I examine not only the tasks that are derived from linguists' needs and goals but also the technologies that appropriately deal with the properties of linguistic data. This research results in the implementation of DAMIEN, an online workbench designed to conduct linguistic experiments on corpora.Financial support for this research has been provided by the DGI, Spanish Ministry of Education and Science, grant FFI2014-53788-C3-1-P.Periñán Pascual, C. (2017). Bridging the gap within text-data analytics: A computer environment for data analysis in linguistic research. LFE. Revista de Lenguas para Fines Específicos. 23(2):111-132. https://doi.org/10.20420/rlfe.2017.175S11113223

    The dicode workbench: A flexible framework for the integration of information and web services

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    Aiming to address requirements concerning integration of services in the context of ?big data?, this paper presents an innovative approach that (i) ensures a flexible, adaptable and scalable information and computation infrastructure, and (ii) exploits the competences of stakeholders and information workers to meaningfully confront information management issues such as information characterization, classification and interpretation, thus incorporating the underlying collective intelligence. Our approach pays much attention to the issues of usability and ease-of-use, not requiring any particular programming expertise from the end users. We report on a series of technical issues concerning the desired flexibility of the proposed integration framework and we provide related recommendations to developers of such solutions. Evaluation results are also discussed

    The Artificial Intelligence Workbench: a retrospective review

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    Last decade, biomedical and bioinformatics researchers have been demanding advanced and user-friendly applications for real use in practice. In this context, the Artificial Intelligence Workbench, an open-source Java desktop application framework for scientific software development, emerged with the goal of provid-ing support to both fundamental and applied research in the domain of transla-tional biomedicine and bioinformatics. AIBench automatically provides function-alities that are common to scientific applications, such as user parameter defini-tion, logging facilities, multi-threading execution, experiment repeatability, work-flow management, and fast user interface development, among others. Moreover, AIBench promotes a reusable component based architecture, which also allows assembling new applications by the reuse of libraries from existing projects or third-party software. Ten years have passed since the first release of AIBench, so it is time to look back and check if it has fulfilled the purposes for which it was conceived to and how it evolved over time

    Sentiment analysis using KNIME: a systematic literature review of big data logistics

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    Text analytics and sentiment analysis can help researchers to derive potentially valuable thematic and narrative insights from text-based content such as industry reviews, leading OM and OR journal articles and government reports. The classification system described here analyses the opinions of the performance of various public and private, manufacturing, medical, service and retail organizations in integrating big data into their logistics. It explains methods of data collection and the sentiment analysis process for classifying big data logistics literature using KNIME. Finally, it then gives an overview of the differences and explores future possibilities in sentiment analysis for investigating different industrial sectors and data sources

    Data mining and fusion

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    Realistic electronic books

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    People like books. They are convenient and can be accessed easily and enjoyably. In contrast, many view the experience of accessing and exploring electronic documents as dull, cumbersome and disorientating. This thesis claims that modelling digital documents as physical books can significantly improve reading performance. To investigate this claim, a realistic electronic book model was developed and evaluated. In this model, a range of properties associated with physical books---analogue page turning, bookmarks and annotations---are emulated. Advantage is also taken of the digital environment by supporting hyperlinks, multimedia, full-text search over terms and synonyms, automatically cross referencing documents with an online encyclopaedia, and producing a back-of-the-book index. The main technical challenge of simulating physical books is finding a suitable technique for page turning that is sufficiently realistic, yet lightweight, responsive, scalable and accessible. Several techniques were surveyed, implemented and evaluated. The chosen technique allows realistic books to be presented in the Adobe Flash Player, the most widely used browser plug-in on the Web. A series of usability studies were conducted to compare reading performance while performing various tasks with HTML, PDF, physical books, and simulated books. They revealed that participants not only preferred the new interface, but completed the tasks more efficiently, without any loss in accuracy
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