28 research outputs found

    Overcoming the Imbalance Between Tag Recommendation Approaches and Real-World Folksonomy Structures with Cognitive-Inspired Algorithms

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    In this paper, we study the imbalance between current state-of-the-art tag recommendation algorithms and the folksonomy structures of real-world social tagging systems. While algorithms such as FolkRank are designed for dense folksonomy structures, most social tagging systems exhibit a sparse nature. To overcome this imbalance, we show that cognitive-inspired algorithms, which model the tag vocabulary of a user in a cognitive-plausible way, can be helpful. Our present approach does this via implementing the activation equation of the cognitive architecture ACT-R, which determines the usefulness of units in human memory (e.g., tags). In this sense, our long-term research goal is to design hybrid recommendation approaches, which combine the advantages of both worlds in order to adapt to the current setting (i.e., sparse vs. dense ones).Comment: Presented at the European Symposium for Computational Social Science

    Social search in collaborative tagging networks : the role of ties

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    [no abstract

    Applying Wikipedia to Interactive Information Retrieval

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    There are many opportunities to improve the interactivity of information retrieval systems beyond the ubiquitous search box. One idea is to use knowledge bases—e.g. controlled vocabularies, classification schemes, thesauri and ontologies—to organize, describe and navigate the information space. These resources are popular in libraries and specialist collections, but have proven too expensive and narrow to be applied to everyday webscale search. Wikipedia has the potential to bring structured knowledge into more widespread use. This online, collaboratively generated encyclopaedia is one of the largest and most consulted reference works in existence. It is broader, deeper and more agile than the knowledge bases put forward to assist retrieval in the past. Rendering this resource machine-readable is a challenging task that has captured the interest of many researchers. Many see it as a key step required to break the knowledge acquisition bottleneck that crippled previous efforts. This thesis claims that the roadblock can be sidestepped: Wikipedia can be applied effectively to open-domain information retrieval with minimal natural language processing or information extraction. The key is to focus on gathering and applying human-readable rather than machine-readable knowledge. To demonstrate this claim, the thesis tackles three separate problems: extracting knowledge from Wikipedia; connecting it to textual documents; and applying it to the retrieval process. First, we demonstrate that a large thesaurus-like structure can be obtained directly from Wikipedia, and that accurate measures of semantic relatedness can be efficiently mined from it. Second, we show that Wikipedia provides the necessary features and training data for existing data mining techniques to accurately detect and disambiguate topics when they are mentioned in plain text. Third, we provide two systems and user studies that demonstrate the utility of the Wikipedia-derived knowledge base for interactive information retrieval

    Social informatics

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    5th International Conference, SocInfo 2013, Kyoto, Japan, November 25-27, 2013, Proceedings</p

    Semantic discovery and reuse of business process patterns

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    Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

    Information Management for Digital Learners : Introduction, Challenges, and Concepts of Personal Information Management for Individual Learners

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    The current cultural transition of our society into a digital society influences all aspects of human life. New technologies like the Internet and mobile devices enable an unobstructed access to knowledge in worldwide networks. These advancements bring with them a great freedom in decisions and actions of individuals but also a growing demand for an appropriate mastering of this freedom of choice and the amount of knowledge that has become available today. Naturally, this observable rise and progress of new technologies—gently but emphatically becoming part of people’s everyday lives—not only changes the way people work, communicate, and shape their leisure but also the way people learn. This thesis is dedicated to an examination of how learners can meet these requirements with the support that modern technology is able to provide to learners. More precisely, this thesis places a particular emphasis that is absent from previous work in the field and thus makes it distinctive: the explicit focus on individual learners. As a result, the main concern of this thesis can be described as the examination, development, and implementation of personal information management in learning. Altogether two different steps towards a solution have been chosen: the development of a theoretical framework and its practical implementation into a comprehensive concept. To establish a theoretical framework for personal information management in learning, the spheres of learning, e-learning, and personalised learning have been combined with theories of organisational and personal knowledge management to form a so far unique holistic view of personal information management in learning. The development of this framework involves the identification of characteristics, needs, and challenges that distinguish individual learners from within the larger crowd of uniform learners. The theoretical framework defined within the first part is transferred to a comprehensive technical concept for personal information management in learning. The realisation and design of this concept as well as its practical implementation are strongly characterised by the utilisation of information retrieval techniques to support individual learners. The characteristic feature of the resulting system is a flexible architecture that enables the unified acquisition, representation, and organisation of information related to an individual’s learning and supports an improved find-ability of personal information across all relevant sources of information. The most important results of this thesis have been validated by a comparison with current projects in related areas and within a user study.Der gegenwärtige Wandel unserer Gesellschaft zu einer digitalen Gesellschaft hat weitreichenden Einfluss auf alle Aspekte des menschlichen Lebens. Neue Technologien wie das Internet und mobile Geräte zur Nutzung dieser Technologien ermöglichen einen nahezu ungehinderten Zugriff auf Wissen in weltweiten Netzwerken. Dieser Fortschritt bringt einerseits einen großen Freiheitsgrad für Entscheidungen und Handlungen des Einzelnen, andererseits aber auch eine immer lauter werdende Forderung nach Strategien für einen adäquaten Umgang mit dieser Freiheit und der verfügbaren Menge an Informationen. Naturgemäß verändern dieser Fortschritt und die zugehörigen Technologien nicht nur unser Arbeitsleben und den privaten Alltag, sondern auch die Art und Weise zu lernen. Diese Arbeit beschäftigt sich mit der Frage, wie Lernende diesen neuen Anforderungen gerecht werden und mithilfe von modernen Technologien in einem adäquaten Informationsmanagement unterstützt werden können. Die Besonderheit liegt dabei in einem ausschließlichen Fokus individuell Lernender, genauer gesagt jenen, die sich eigenständig auf individuellen Lernpfaden bewegen. Zusammengefasst untersucht diese Arbeit daher Möglichkeiten des personalisierten Informationsmanagements für Lernende. Die Untersuchung dieser Fragestellung erfolgt auf zwei Ebenen. Die erste Ebene dieser Arbeit umfasst eine theoretische Untersuchung der Thematik. Zu diesem Zweck wird ein übergreifendes Rahmenwerk für das persönliche Informationsmanagement von Lernenden entwickelt, das eine ganzheitliche Betrachtung dieser Fragestellung ermöglicht. Das entwickelte Rahmenwerk zeichnet sich insbesondere durch eine Verschmelzung der Domänen E-Learning und Wissensmanagement aus. Dazu werden im Rahmen dieser theoretischen Untersuchung prägende Facetten des Lernens beschrieben und Theorien des organisatorischen Wissensmanagements zur Bewältigung des persönlichen Informationsmanagements untersucht. Dies führt schließlich zu einer Charakterisierung von individuell Lernenden, der Identifikation grundlegender Herausforderungen für diese Lernenden sowie einem Modell zur Beschreibung des individuellen Informations- und Wissensmanagements. Die zweite Ebene dieser Arbeit umfasst die Umsetzung des entwickelten Rahmenwerks in ein praktisches Konzept zur effizienten Verwaltung von persönlichen Lerninhalten und -informationen einzelner Lernender. Das realisierte System ist dabei durch die Berücksichtigung von Informationsbedürfnissen individuell Lernender sowie besonders durch den gezielten Einsatz von Information Retrieval Techniken zur Unterstützung dieser Lernenden gekennzeichnet. Das konstituierende Merkmal dieses Systems ist daher eine flexible Architektur, die die Erfassung von Lernobjekten unter besonderer Berücksichtigung des Lernkontexts erlaubt. Detaillierter betrachtet ermöglicht die Erfassung von Basisinformation in Form von Lernobjekten in Kombination mit hierarchischen und nicht-hierarchischen Zusatzinformationen eine individuelle und umfassende Verwaltung von Lerninhalten und -informationen, die auch eine verbesserte Wiederauffindbarkeit dieser Informationen zu einem späteren Zeitpunkt unterstützt. Die wichtigsten Ergebnisse dieser Arbeit werden aktuellen Entwicklungen und Projekten in verwandten Bereichen gegenübergestellt und im Rahmen einer Nutzerstudie grundlegend validiert

    The Future of Information Sciences : INFuture2009 : Digital Resources and Knowledge Sharing

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    Interrogating Datafication

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    What constitutes a data practice and how do contemporary digital media technologies reconfigure our understanding of practices in general? Autonomously acting media, distributed digital infrastructures, and sensor-based media environments challenge the conditions of accounting for data practices both theoretically and empirically. Which forms of cooperation are constituted in and by data practices? And how are human and nonhuman agencies distributed and interrelated in data-saturated environments? The volume collects theoretical, empirical, and historiographical contributions from a range of international scholars to shed light on the current shift from media to data practices

    Interrogating Datafication: Towards a Praxeology of Data

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    What constitutes a data practice and how do contemporary digital media technologies reconfigure our understanding of practices in general? Autonomously acting media, distributed digital infrastructures, and sensor-based media environments challenge the conditions of accounting for data practices both theoretically and empirically. Which forms of cooperation are constituted in and by data practices? And how are human and nonhuman agencies distributed and interrelated in data-saturated environments? The volume collects theoretical, empirical, and historiographical contributions from a range of international scholars to shed light on the current shift from media to data practices
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