1. Building on the Synergy of Machine and Human Reasoning to Tackle Data-Intensive Collaboration and Decision Making

    This paper reports on a hybrid approach aiming to facilitate and augment collaboration and decision making in data-intensive and cognitively-complex settings. The proposed approach exploits and builds on the most prominent high-performance computing paradigms and large data processing technologies to meaningfully search, analyze and aggregate data existing in diverse, extremely large and rapidly evolving sources. It can be viewed as an innovative workbench incorporating and orchestrating a set of interoperable services that reduce the data-intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and concentrate on creative activities. Content Type ...
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD
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