6,292 research outputs found

    Discovering Knowledge through Highly Interactive Information Based Systems

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    [EN] The new Internet era has increased a production of digital data. The mankind had an easy way to the knowledge access never before, but at the same time the rapidly increasing rate of new data, the ease of duplication and transmission of these data across the Net, the new available channels for information dissemination, the large amounts of historical data, questionable quality of the existing data and so on are issues for information overload that causes more difficult to make decision using the right data. Soft-computing techniques for decision support systems and business intelligent systems present pretty interesting and necessary solutions for data management and supporting decision-making processes, but the last step at the decision chain is usually supported by a human agent that has to process the system outcomes in form of reports or visualizations. These kinds of information representations are not enough to make decisions because of behind them could be hidden information patterns that are not obvious for automatic data processing and humans must interact with these data representation in order to discover knowledge. According to this, the current special issue is devoted to present nine experiences that combine visualization and visual analytics techniques, data mining methods, intelligent recommendation agents, user centered evaluation and usability patterns, etc. in interactive systems as a key issue for knowledge discovering in advanced and emerging information systems.[ES] La nueva era de Internet ha aumentado la producción de datos digitales. Nunca nates la humanidad ha tenido una manera más fácil el acceso a los conocimientos, pero al mismo tiempo el rápido aumento de la tasa de nuevos datos, la facilidad de duplicación y transmisión de estos datos a través de la red, los nuevos canales disponibles para la difusión de información, las grandes cantidades de los datos históricos, cuestionable calidad de los datos existentes y así sucesivamente, son temas de la sobrecarga de información que hace más difícil tomar decisiones con la información correcta. Técnicas de Soft-computing para los sistemas de apoyo a las decisiones y sistemas inteligentes de negocios presentan soluciones muy interesantes y necesarias para la gestión de datos y procesos de apoyo a la toma de decisiones, pero el último paso en la cadena de decisiones suele ser apoyados por un agente humano que tiene que procesar los resultados del sistema de en forma de informes o visualizaciones. Este tipo de representaciones de información no son suficientes para tomar decisiones debido detrás de ellos podrían ser patrones de información ocultos que no son obvios para el procesamiento automático de datos y los seres humanos deben interactuar con estos representación de datos con el fin de descubrir el conocimiento. De acuerdo con esto, el presente número especial está dedicado a nueve experiencias actuales que combinan técnicas de visualización y de análisis visual, métodos de minería de datos, agentes de recomendación inteligentes y evaluación centrada en el usuario y patrones de usabilidad, etc. En sistemas interactivos como un tema clave para el descubrimiento de conocimiento en los sistemas de información avanzados y emergentes

    Living Innovation Laboratory Model Design and Implementation

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    Living Innovation Laboratory (LIL) is an open and recyclable way for multidisciplinary researchers to remote control resources and co-develop user centered projects. In the past few years, there were several papers about LIL published and trying to discuss and define the model and architecture of LIL. People all acknowledge about the three characteristics of LIL: user centered, co-creation, and context aware, which make it distinguished from test platform and other innovation approaches. Its existing model consists of five phases: initialization, preparation, formation, development, and evaluation. Goal Net is a goal-oriented methodology to formularize a progress. In this thesis, Goal Net is adopted to subtract a detailed and systemic methodology for LIL. LIL Goal Net Model breaks the five phases of LIL into more detailed steps. Big data, crowd sourcing, crowd funding and crowd testing take place in suitable steps to realize UUI, MCC and PCA throughout the innovation process in LIL 2.0. It would become a guideline for any company or organization to develop a project in the form of an LIL 2.0 project. To prove the feasibility of LIL Goal Net Model, it was applied to two real cases. One project is a Kinect game and the other one is an Internet product. They were both transformed to LIL 2.0 successfully, based on LIL goal net based methodology. The two projects were evaluated by phenomenography, which was a qualitative research method to study human experiences and their relations in hope of finding the better way to improve human experiences. Through phenomenographic study, the positive evaluation results showed that the new generation of LIL had more advantages in terms of effectiveness and efficiency.Comment: This is a book draf

    Sensoring a Generative System to Create User-Controlled Melodies

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    [EN] The automatic generation of music is an emergent field of research that has attracted the attention of countless researchers. As a result, there is a broad spectrum of state of the art research in this field. Many systems have been designed to facilitate collaboration between humans and machines in the generation of valuable music. This research proposes an intelligent system that generates melodies under the supervision of a user, who guides the process through a mechanical device. The mechanical device is able to capture the movements of the user and translate them into a melody. The system is based on a Case-Based Reasoning (CBR) architecture, enabling it to learn from previous compositions and to improve its performance over time. The user uses a device that allows them to adapt the composition to their preferences by adjusting the pace of a melody to a specific context or generating more serious or acute notes. Additionally, the device can automatically resist some of the user’s movements, this way the user learns how they can create a good melody. Several experiments were conducted to analyze the quality of the system and the melodies it generates. According to the users’ validation, the proposed system can generate music that follows a concrete style. Most of them also believed that the partial control of the device was essential for the quality of the generated music

    Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis

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    Product recommendation and preference tracking systems have been adopted extensively in e-commerce businesses. However, the heterogeneity of product attributes results in undesired impediment for an efficient yet personalized e-commerce product brokering. Amid the assortment of product attributes, there are some intrinsic generic attributes having significant relation to a customer’s generic preference. This paper proposes a novel approach in the detection of generic product attributes through feature analysis. The objective is to provide an insight to the understanding of customers’ generic preference. Furthermore, a genetic algorithm is used to find the suitable feature weight set, hence reducing the rate of misclassification. A prototype has been implemented and the experimental results are promising

    A Chatbot Solution for eGLU-Box Pro: The Usability Evaluation Platform for Italian Public Administrations

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    This paper shows a chatbot solution for eGLU-box Pro, a usability testing platform for Italian Public Administration (PA). eGLU-box Pro is a web-based tool designed to help PA practitioners in creating remote usability tests and analyzing participants’ answers and interaction data after they complete the usability tasks. The impact of the chatbot solution on users’ experience was assessed by bio-behavioral evaluation methods such as eye tracking, electroencephalography, and facial expression recognition. This work describes the platform and its integrated chatbot solution and shows the results of a preliminary laboratory study involving 20 end-users. The study is part of an ongoing design and development project based on a user-centered approach

    How do bidders’ organism reactions mediate auction stimuli and bidder loyalty in online auctions? The case of Taobao in China

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    © 2016 Elsevier B.V.Currently, it is critical to nurture bidder loyalty in the highly competitive online auction business. This study investigated the mediating effect of consumer perceptions between technological/brand stimuli and bidder loyalty to an online auction website by applying the traditional and evolutionary stimulus-organism-response models. We tested these models using 449 bidders from Taobao, an online auction service provider in China. Based on the results of covariance-based structural equation modelling, we showed that consumer perceptions fully mediate technological stimuli, but only partially mediate brand stimuli, and bidder loyalty. These results can be used to further improve the related research and practice.Link_to_subscribed_fulltex

    A Multi-Agent Architecture for An Intelligent Web-Based Educational System

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    An intelligent educational system must constitute an adaptive system built on multi-agent system architecture. The multi-agent architecture component provides self-organization, self-direction, and other control functionalities that are crucially important for an educational system. On the other hand, the adaptiveness of the system is necessary to provide customization, diversification, and interactional functionalities. Therefore, an educational system architecture that integrates multi-agent functionality [50] with adaptiveness can offer the learner the required independent learning experience. An educational system architecture is a complex structure with an intricate hierarchal organization where the functional components of the system undergo sophisticated and unpredictable internal interactions to perform its function. Hence, the system architecture must constitute adaptive and autonomous agents differentiated according to their functions, called multi-agent systems (MASs). The research paper proposes an adaptive hierarchal multi-agent educational system (AHMAES) [51] as an alternative to the traditional education delivery method. The document explains the various architectural characteristics of an adaptive multi-agent educational system and critically analyzes the system’s factors for software quality attributes

    The Evolution of Technology in Call Centers

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    Historical research was conducted through literature. The report traces the evolution of technology in call centers (CCs) from their early inception to 2018. CCs are integrated into many facets of multidisciplinary areas of business, industry, and public and private institutions of higher education. Three research questions were addressed: What technologies enabled the start of CCs? How did the communications between customers and CSRs take place? What was the content of the earlier communications? How did services and communications evolve as technology matured? What are the current state-of-the-art technologies that exist in CCs? Which industries appear to have the best solutions? What are these solutions? Photograph Analysis Worksheets and Written Document Analysis Worksheets from the National Archives and Records Administration were used to analyze primary source materials. Also, used were Primary Source Analysis Tools from the Library of Congress. The final report offers a comprehensive history of the technology evolution within the industry. Included are a discussion of state-of-the-art technologies, the range of their applications and suggestions for staff training
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