5,762 research outputs found

    Smart Conversational Agents for Reminiscence

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    In this paper we describe the requirements and early system design for a smart conversational agent that can assist older adults in the reminiscence process. The practice of reminiscence has well documented benefits for the mental, social and emotional well-being of older adults. However, the technology support, valuable in many different ways, is still limited in terms of need of co-located human presence, data collection capabilities, and ability to support sustained engagement, thus missing key opportunities to improve care practices, facilitate social interactions, and bring the reminiscence practice closer to those with less opportunities to engage in co-located sessions with a (trained) companion. We discuss conversational agents and cognitive services as the platform for building the next generation of reminiscence applications, and introduce the concept application of a smart reminiscence agent

    Collective awareness platforms and digital social innovation mediating consensus seeking in problem situations

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    In this paper we show the results of our studies carried out in the framework of the European Project SciCafe2.0 in the area of Participatory Engagement models. We present a methodological approach built on participative engagements models and holistic framework for problem situation clarification and solution impacts assessment. Several online platforms for social engagement have been analysed to extract the main patterns of participative engagement. We present our own experiments through the SciCafe2.0 Platform and our insights from requirements elicitation

    A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

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    In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-looking conclusion

    Psychological Projections in the Emergence of Hive Mind

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    Innovative community-based computing for entrepreneurship

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    There are many reasons why people all over the world venture out to become entrepreneurs each year but many failed. One of the main reasons for failure is due to uninformed and lack of advice decisions and actions made by the inexperienced entrepreneurs. To support their inexperience, education, decision support systems and a virtual intelligence network could be established but these strategies have limitations. This paper discusses the possibility of using community-based computing to support entrepreneurship and how entrepreneurs could benefit from the collaboration

    Crowdsourcing a Word-Emotion Association Lexicon

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    Even though considerable attention has been given to the polarity of words (positive and negative) and the creation of large polarity lexicons, research in emotion analysis has had to rely on limited and small emotion lexicons. In this paper we show how the combined strength and wisdom of the crowds can be used to generate a large, high-quality, word-emotion and word-polarity association lexicon quickly and inexpensively. We enumerate the challenges in emotion annotation in a crowdsourcing scenario and propose solutions to address them. Most notably, in addition to questions about emotions associated with terms, we show how the inclusion of a word choice question can discourage malicious data entry, help identify instances where the annotator may not be familiar with the target term (allowing us to reject such annotations), and help obtain annotations at sense level (rather than at word level). We conducted experiments on how to formulate the emotion-annotation questions, and show that asking if a term is associated with an emotion leads to markedly higher inter-annotator agreement than that obtained by asking if a term evokes an emotion
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